pandas索引index

pandas索引

html { font-family: sans-serif }
body { margin: 0 }
article,aside,details,figcaption,figure,footer,header,hgroup,main,menu,nav,section,summary { display: block }
audio,canvas,progress,video { display: inline-block; vertical-align: baseline }
audio:not([controls]) { display: none; height: 0 }
[hidden],template { display: none }
a { background-color: transparent }
a:active,a:hover { outline: 0 }
abbr[title] { border-bottom: 1px dotted }
b,strong { font-weight: bold }
dfn { font-style: italic }
h1 { font-size: 2em; margin: 0.67em 0 }
mark { background: #ff0; color: #000 }
small { font-size: 80% }
sub,sup { font-size: 75%; line-height: 0; position: relative; vertical-align: baseline }
sup { top: -0.5em }
sub { bottom: -0.25em }
img { border: 0 }
svg:not(:root) { overflow: hidden }
figure { margin: 1em 40px }
hr { height: 0 }
pre { overflow: auto }
code,kbd,pre,samp { font-family: monospace, monospace; font-size: 1em }
button,input,optgroup,select,textarea { color: inherit; font: inherit; margin: 0 }
button { overflow: visible }
button,select { text-transform: none }
button,html input[type="button"],input[type="reset"],input[type="submit"] { cursor: pointer }
button[disabled],html input[disabled] { cursor: default }
button::-moz-focus-inner,
input::-moz-focus-inner { border: 0; padding: 0 }
input { line-height: normal }
input[type="checkbox"],input[type="radio"] { padding: 0 }
input[type="number"]::-webkit-inner-spin-button,
input[type="number"]::-webkit-outer-spin-button { height: auto }
input[type="search"] { }
input[type="search"]::-webkit-search-cancel-button,
input[type="search"]::-webkit-search-decoration { }
fieldset { border: 1px solid #c0c0c0; margin: 0 2px; padding: 0.35em 0.625em 0.75em }
legend { border: 0; padding: 0 }
textarea { overflow: auto }
optgroup { font-weight: bold }
table { border-collapse: collapse; border-spacing: 0 }
td,th { padding: 0 }
.glyphicon { position: relative; top: 1px; display: inline-block; font-family: "Glyphicons Halflings"; font-style: normal; font-weight: normal; line-height: 1 }
.glyphicon-asterisk::before { content: "*" }
.glyphicon-plus::before { content: "+" }
.glyphicon-euro::before,.glyphicon-eur::before { content: "€" }
.glyphicon-minus::before { content: "?" }
.glyphicon-cloud::before { content: "?" }
.glyphicon-envelope::before { content: "?" }
.glyphicon-pencil::before { content: "?" }
.glyphicon-glass::before { content: "" }
.glyphicon-music::before { content: "" }
.glyphicon-search::before { content: "" }
.glyphicon-heart::before { content: "" }
.glyphicon-star::before { content: "" }
.glyphicon-star-empty::before { content: "" }
.glyphicon-user::before { content: "" }
.glyphicon-film::before { content: "" }
.glyphicon-th-large::before { content: "" }
.glyphicon-th::before { content: "" }
.glyphicon-th-list::before { content: "" }
.glyphicon-ok::before { content: "" }
.glyphicon-remove::before { content: "" }
.glyphicon-zoom-in::before { content: "" }
.glyphicon-zoom-out::before { content: "" }
.glyphicon-off::before { content: "" }
.glyphicon-signal::before { content: "" }
.glyphicon-cog::before { content: "" }
.glyphicon-trash::before { content: "" }
.glyphicon-home::before { content: "" }
.glyphicon-file::before { content: "" }
.glyphicon-time::before { content: "" }
.glyphicon-road::before { content: "" }
.glyphicon-download-alt::before { content: "" }
.glyphicon-download::before { content: "" }
.glyphicon-upload::before { content: "" }
.glyphicon-inbox::before { content: "" }
.glyphicon-play-circle::before { content: "" }
.glyphicon-repeat::before { content: "" }
.glyphicon-refresh::before { content: "" }
.glyphicon-list-alt::before { content: "" }
.glyphicon-lock::before { content: "" }
.glyphicon-flag::before { content: "" }
.glyphicon-headphones::before { content: "" }
.glyphicon-volume-off::before { content: "" }
.glyphicon-volume-down::before { content: "" }
.glyphicon-volume-up::before { content: "" }
.glyphicon-qrcode::before { content: "" }
.glyphicon-barcode::before { content: "" }
.glyphicon-tag::before { content: "" }
.glyphicon-tags::before { content: "" }
.glyphicon-book::before { content: "" }
.glyphicon-bookmark::before { content: "" }
.glyphicon-print::before { content: "" }
.glyphicon-camera::before { content: "" }
.glyphicon-font::before { content: "" }
.glyphicon-bold::before { content: "" }
.glyphicon-italic::before { content: "" }
.glyphicon-text-height::before { content: "" }
.glyphicon-text-width::before { content: "" }
.glyphicon-align-left::before { content: "" }
.glyphicon-align-center::before { content: "" }
.glyphicon-align-right::before { content: "" }
.glyphicon-align-justify::before { content: "" }
.glyphicon-list::before { content: "" }
.glyphicon-indent-left::before { content: "" }
.glyphicon-indent-right::before { content: "" }
.glyphicon-facetime-video::before { content: "" }
.glyphicon-picture::before { content: "" }
.glyphicon-map-marker::before { content: "" }
.glyphicon-adjust::before { content: "" }
.glyphicon-tint::before { content: "" }
.glyphicon-edit::before { content: "" }
.glyphicon-share::before { content: "" }
.glyphicon-check::before { content: "" }
.glyphicon-move::before { content: "" }
.glyphicon-step-backward::before { content: "" }
.glyphicon-fast-backward::before { content: "" }
.glyphicon-backward::before { content: "" }
.glyphicon-play::before { content: "" }
.glyphicon-pause::before { content: "" }
.glyphicon-stop::before { content: "" }
.glyphicon-forward::before { content: "" }
.glyphicon-fast-forward::before { content: "" }
.glyphicon-step-forward::before { content: "" }
.glyphicon-eject::before { content: "" }
.glyphicon-chevron-left::before { content: "" }
.glyphicon-chevron-right::before { content: "" }
.glyphicon-plus-sign::before { content: "" }
.glyphicon-minus-sign::before { content: "" }
.glyphicon-remove-sign::before { content: "" }
.glyphicon-ok-sign::before { content: "" }
.glyphicon-question-sign::before { content: "" }
.glyphicon-info-sign::before { content: "" }
.glyphicon-screenshot::before { content: "" }
.glyphicon-remove-circle::before { content: "" }
.glyphicon-ok-circle::before { content: "" }
.glyphicon-ban-circle::before { content: "" }
.glyphicon-arrow-left::before { content: "" }
.glyphicon-arrow-right::before { content: "" }
.glyphicon-arrow-up::before { content: "" }
.glyphicon-arrow-down::before { content: "" }
.glyphicon-share-alt::before { content: "" }
.glyphicon-resize-full::before { content: "" }
.glyphicon-resize-small::before { content: "" }
.glyphicon-exclamation-sign::before { content: "" }
.glyphicon-gift::before { content: "" }
.glyphicon-leaf::before { content: "" }
.glyphicon-fire::before { content: "" }
.glyphicon-eye-open::before { content: "" }
.glyphicon-eye-close::before { content: "" }
.glyphicon-warning-sign::before { content: "" }
.glyphicon-plane::before { content: "" }
.glyphicon-calendar::before { content: "" }
.glyphicon-random::before { content: "" }
.glyphicon-comment::before { content: "" }
.glyphicon-magnet::before { content: "" }
.glyphicon-chevron-up::before { content: "" }
.glyphicon-chevron-down::before { content: "" }
.glyphicon-retweet::before { content: "" }
.glyphicon-shopping-cart::before { content: "" }
.glyphicon-folder-close::before { content: "" }
.glyphicon-folder-open::before { content: "" }
.glyphicon-resize-vertical::before { content: "" }
.glyphicon-resize-horizontal::before { content: "" }
.glyphicon-hdd::before { content: "" }
.glyphicon-bullhorn::before { content: "" }
.glyphicon-bell::before { content: "" }
.glyphicon-certificate::before { content: "" }
.glyphicon-thumbs-up::before { content: "" }
.glyphicon-thumbs-down::before { content: "" }
.glyphicon-hand-right::before { content: "" }
.glyphicon-hand-left::before { content: "" }
.glyphicon-hand-up::before { content: "" }
.glyphicon-hand-down::before { content: "" }
.glyphicon-circle-arrow-right::before { content: "" }
.glyphicon-circle-arrow-left::before { content: "" }
.glyphicon-circle-arrow-up::before { content: "" }
.glyphicon-circle-arrow-down::before { content: "" }
.glyphicon-globe::before { content: "" }
.glyphicon-wrench::before { content: "" }
.glyphicon-tasks::before { content: "" }
.glyphicon-filter::before { content: "" }
.glyphicon-briefcase::before { content: "" }
.glyphicon-fullscreen::before { content: "" }
.glyphicon-dashboard::before { content: "" }
.glyphicon-paperclip::before { content: "" }
.glyphicon-heart-empty::before { content: "" }
.glyphicon-link::before { content: "" }
.glyphicon-phone::before { content: "" }
.glyphicon-pushpin::before { content: "" }
.glyphicon-usd::before { content: "" }
.glyphicon-gbp::before { content: "" }
.glyphicon-sort::before { content: "" }
.glyphicon-sort-by-alphabet::before { content: "" }
.glyphicon-sort-by-alphabet-alt::before { content: "" }
.glyphicon-sort-by-order::before { content: "" }
.glyphicon-sort-by-order-alt::before { content: "" }
.glyphicon-sort-by-attributes::before { content: "" }
.glyphicon-sort-by-attributes-alt::before { content: "" }
.glyphicon-unchecked::before { content: "" }
.glyphicon-expand::before { content: "" }
.glyphicon-collapse-down::before { content: "" }
.glyphicon-collapse-up::before { content: "" }
.glyphicon-log-in::before { content: "" }
.glyphicon-flash::before { content: "" }
.glyphicon-log-out::before { content: "" }
.glyphicon-new-window::before { content: "" }
.glyphicon-record::before { content: "" }
.glyphicon-save::before { content: "" }
.glyphicon-open::before { content: "" }
.glyphicon-saved::before { content: "" }
.glyphicon-import::before { content: "" }
.glyphicon-export::before { content: "" }
.glyphicon-send::before { content: "" }
.glyphicon-floppy-disk::before { content: "" }
.glyphicon-floppy-saved::before { content: "" }
.glyphicon-floppy-remove::before { content: "" }
.glyphicon-floppy-save::before { content: "" }
.glyphicon-floppy-open::before { content: "" }
.glyphicon-credit-card::before { content: "" }
.glyphicon-transfer::before { content: "" }
.glyphicon-cutlery::before { content: "" }
.glyphicon-header::before { content: "" }
.glyphicon-compressed::before { content: "" }
.glyphicon-earphone::before { content: "" }
.glyphicon-phone-alt::before { content: "" }
.glyphicon-tower::before { content: "" }
.glyphicon-stats::before { content: "" }
.glyphicon-sd-video::before { content: "" }
.glyphicon-hd-video::before { content: "" }
.glyphicon-subtitles::before { content: "" }
.glyphicon-sound-stereo::before { content: "" }
.glyphicon-sound-dolby::before { content: "" }
.glyphicon-sound-5-1::before { content: "" }
.glyphicon-sound-6-1::before { content: "" }
.glyphicon-sound-7-1::before { content: "" }
.glyphicon-copyright-mark::before { content: "" }
.glyphicon-registration-mark::before { content: "" }
.glyphicon-cloud-download::before { content: "" }
.glyphicon-cloud-upload::before { content: "" }
.glyphicon-tree-conifer::before { content: "" }
.glyphicon-tree-deciduous::before { content: "" }
.glyphicon-cd::before { content: "" }
.glyphicon-save-file::before { content: "" }
.glyphicon-open-file::before { content: "" }
.glyphicon-level-up::before { content: "" }
.glyphicon-copy::before { content: "" }
.glyphicon-paste::before { content: "" }
.glyphicon-alert::before { content: "" }
.glyphicon-equalizer::before { content: "" }
.glyphicon-king::before { content: "" }
.glyphicon-queen::before { content: "" }
.glyphicon-pawn::before { content: "" }
.glyphicon-bishop::before { content: "" }
.glyphicon-knight::before { content: "" }
.glyphicon-baby-formula::before { content: "" }
.glyphicon-tent::before { content: "?" }
.glyphicon-blackboard::before { content: "" }
.glyphicon-bed::before { content: "" }
.glyphicon-apple::before { content: "?" }
.glyphicon-erase::before { content: "" }
.glyphicon-hourglass::before { content: "?" }
.glyphicon-lamp::before { content: "" }
.glyphicon-duplicate::before { content: "" }
.glyphicon-piggy-bank::before { content: "" }
.glyphicon-scissors::before { content: "" }
.glyphicon-bitcoin::before { content: "" }
.glyphicon-btc::before { content: "" }
.glyphicon-xbt::before { content: "" }
.glyphicon-yen::before { content: "￥" }
.glyphicon-jpy::before { content: "￥" }
.glyphicon-ruble::before { content: "?" }
.glyphicon-rub::before { content: "?" }
.glyphicon-scale::before { content: "" }
.glyphicon-ice-lolly::before { content: "" }
.glyphicon-ice-lolly-tasted::before { content: "" }
.glyphicon-education::before { content: "" }
.glyphicon-option-horizontal::before { content: "" }
.glyphicon-option-vertical::before { content: "" }
.glyphicon-menu-hamburger::before { content: "" }
.glyphicon-modal-window::before { content: "" }
.glyphicon-oil::before { content: "" }
.glyphicon-grain::before { content: "" }
.glyphicon-sunglasses::before { content: "" }
.glyphicon-text-size::before { content: "" }
.glyphicon-text-color::before { content: "" }
.glyphicon-text-background::before { content: "" }
.glyphicon-object-align-top::before { content: "" }
.glyphicon-object-align-bottom::before { content: "" }
.glyphicon-object-align-horizontal::before { content: "" }
.glyphicon-object-align-left::before { content: "" }
.glyphicon-object-align-vertical::before { content: "" }
.glyphicon-object-align-right::before { content: "" }
.glyphicon-triangle-right::before { content: "" }
.glyphicon-triangle-left::before { content: "" }
.glyphicon-triangle-bottom::before { content: "" }
.glyphicon-triangle-top::before { content: "" }
.glyphicon-console::before { content: "" }
.glyphicon-superscript::before { content: "" }
.glyphicon-subscript::before { content: "" }
.glyphicon-menu-left::before { content: "" }
.glyphicon-menu-right::before { content: "" }
.glyphicon-menu-down::before { content: "" }
.glyphicon-menu-up::before { content: "" }
* { }
*::before,*::after { }
html { font-size: 10px }
body { font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; font-size: 13px; line-height: 1.42857143; color: #000; background-color: #fff }
input,button,select,textarea { font-family: inherit; font-size: inherit; line-height: inherit }
a { color: #337ab7; text-decoration: none }
a:hover,a:focus { color: #23527c; text-decoration: underline }
a:focus { outline: 5px auto -webkit-focus-ring-color }
figure { margin: 0 }
img { vertical-align: middle }
.img-responsive,.thumbnail>img,.thumbnail a>img,.carousel-inner>.item>img,.carousel-inner>.item>a>img { display: block; max-width: 100%; height: auto }
.img-rounded { }
.img-thumbnail { padding: 4px; line-height: 1.42857143; background-color: #fff; border: 1px solid #ddd; display: inline-block; max-width: 100%; height: auto }
.img-circle { }
hr { margin-top: 18px; margin-bottom: 18px; border: 0; border-top: 1px solid #eeeeee }
.sr-only { position: absolute; width: 1px; height: 1px; margin: -1px; padding: 0; overflow: hidden; clip: rect(0, 0, 0, 0); border: 0 }
.sr-only-focusable:active,.sr-only-focusable:focus { position: static; width: auto; height: auto; margin: 0; overflow: visible; clip: auto }
[role="button"] { cursor: pointer }
h1,h2,h3,h4,h5,h6,.h1,.h2,.h3,.h4,.h5,.h6 { font-family: inherit; font-weight: 500; line-height: 1.1; color: inherit }
h1 small,h2 small,h3 small,h4 small,h5 small,h6 small,.h1 small,.h2 small,.h3 small,.h4 small,.h5 small,.h6 small,h1 .small,h2 .small,h3 .small,h4 .small,h5 .small,h6 .small,.h1 .small,.h2 .small,.h3 .small,.h4 .small,.h5 .small,.h6 .small { font-weight: normal; line-height: 1; color: #777777 }
h1,.h1,h2,.h2,h3,.h3 { margin-top: 18px; margin-bottom: 9px }
h1 small,.h1 small,h2 small,.h2 small,h3 small,.h3 small,h1 .small,.h1 .small,h2 .small,.h2 .small,h3 .small,.h3 .small { font-size: 65% }
h4,.h4,h5,.h5,h6,.h6 { margin-top: 9px; margin-bottom: 9px }
h4 small,.h4 small,h5 small,.h5 small,h6 small,.h6 small,h4 .small,.h4 .small,h5 .small,.h5 .small,h6 .small,.h6 .small { font-size: 75% }
h1,.h1 { font-size: 33px }
h2,.h2 { font-size: 27px }
h3,.h3 { font-size: 23px }
h4,.h4 { font-size: 17px }
h5,.h5 { font-size: 13px }
h6,.h6 { font-size: 12px }
p { margin: 0 0 9px }
.lead { margin-bottom: 18px; font-size: 14px; font-weight: 300; line-height: 1.4 }
small,.small { font-size: 92% }
mark,.mark { background-color: #fcf8e3; padding: .2em }
.text-left { text-align: left }
.text-right { text-align: right }
.text-center { text-align: center }
.text-justify { text-align: justify }
.text-nowrap { white-space: nowrap }
.text-lowercase { text-transform: lowercase }
.text-uppercase { text-transform: uppercase }
.text-capitalize { text-transform: capitalize }
.text-muted { color: #777777 }
.text-primary { color: #337ab7 }
a.text-primary:hover,a.text-primary:focus { color: #286090 }
.text-success { color: #3c763d }
a.text-success:hover,a.text-success:focus { color: #2b542c }
.text-info { color: #31708f }
a.text-info:hover,a.text-info:focus { color: #245269 }
.text-warning { color: #8a6d3b }
a.text-warning:hover,a.text-warning:focus { color: #66512c }
.text-danger { color: #a94442 }
a.text-danger:hover,a.text-danger:focus { color: #843534 }
.bg-primary { color: #fff; background-color: #337ab7 }
a.bg-primary:hover,a.bg-primary:focus { background-color: #286090 }
.bg-success { background-color: #dff0d8 }
a.bg-success:hover,a.bg-success:focus { background-color: #c1e2b3 }
.bg-info { background-color: #d9edf7 }
a.bg-info:hover,a.bg-info:focus { background-color: #afd9ee }
.bg-warning { background-color: #fcf8e3 }
a.bg-warning:hover,a.bg-warning:focus { background-color: #f7ecb5 }
.bg-danger { background-color: #f2dede }
a.bg-danger:hover,a.bg-danger:focus { background-color: #e4b9b9 }
.page-header { padding-bottom: 8px; margin: 36px 0 18px; border-bottom: 1px solid #eeeeee }
ul,ol { margin-top: 0; margin-bottom: 9px }
ul ul,ol ul,ul ol,ol ol { margin-bottom: 0 }
.list-unstyled { padding-left: 0; list-style: none }
.list-inline { padding-left: 0; list-style: none; margin-left: -5px }
.list-inline>li { display: inline-block; padding-left: 5px; padding-right: 5px }
dl { margin-top: 0; margin-bottom: 18px }
dt,dd { line-height: 1.42857143 }
dt { font-weight: bold }
dd { margin-left: 0 }
abbr[title],abbr[data-original-title] { cursor: help; border-bottom: 1px dotted #777777 }
.initialism { font-size: 90%; text-transform: uppercase }
blockquote { padding: 9px 18px; margin: 0 0 18px; font-size: inherit; border-left: 5px solid #eeeeee }
blockquote p:last-child,blockquote ul:last-child,blockquote ol:last-child { margin-bottom: 0 }
blockquote footer,blockquote small,blockquote .small { display: block; font-size: 80%; line-height: 1.42857143; color: #777777 }
blockquote footer::before,blockquote small::before,blockquote .small::before { content: "—?" }
.blockquote-reverse,blockquote.pull-right { padding-right: 15px; padding-left: 0; border-right: 5px solid #eeeeee; border-left: 0; text-align: right }
.blockquote-reverse footer::before,blockquote.pull-right footer::before,.blockquote-reverse small::before,blockquote.pull-right small::before,.blockquote-reverse .small::before,blockquote.pull-right .small::before { content: "" }
.blockquote-reverse footer::after,blockquote.pull-right footer::after,.blockquote-reverse small::after,blockquote.pull-right small::after,.blockquote-reverse .small::after,blockquote.pull-right .small::after { content: "?—" }
address { margin-bottom: 18px; font-style: normal; line-height: 1.42857143 }
code,kbd,pre,samp { font-family: monospace }
code { padding: 2px 4px; font-size: 90%; color: #c7254e; background-color: #f9f2f4 }
kbd { padding: 2px 4px; font-size: 90%; color: #888; background-color: transparent }
kbd kbd { padding: 0; font-size: 100%; font-weight: bold }
pre { display: block; padding: 8.5px; margin: 0 0 9px; font-size: 12px; line-height: 1.42857143; color: #333333; background-color: #f5f5f5; border: 1px solid #ccc }
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.btn-danger { color: #fff; background-color: #d9534f; border-color: #d43f3a }
.btn-danger:focus,.btn-danger.focus { color: #fff; background-color: #c9302c; border-color: #761c19 }
.btn-danger:hover { color: #fff; background-color: #c9302c; border-color: #ac2925 }
.btn-danger:active,.btn-danger.active,.open>.dropdown-toggle.btn-danger { color: #fff; background-color: #c9302c; border-color: #ac2925 }
.btn-danger:active:hover,.btn-danger.active:hover,.open>.dropdown-toggle.btn-danger:hover,.btn-danger:active:focus,.btn-danger.active:focus,.open>.dropdown-toggle.btn-danger:focus,.btn-danger:active.focus,.btn-danger.active.focus,.open>.dropdown-toggle.btn-danger.focus { color: #fff; background-color: #ac2925; border-color: #761c19 }
.btn-danger:active,.btn-danger.active,.open>.dropdown-toggle.btn-danger { background-image: none }
.btn-danger.disabled:hover,.btn-danger[disabled]:hover,fieldset[disabled] .btn-danger:hover,.btn-danger.disabled:focus,.btn-danger[disabled]:focus,fieldset[disabled] .btn-danger:focus,.btn-danger.disabled.focus,.btn-danger[disabled].focus,fieldset[disabled] .btn-danger.focus { background-color: #d9534f; border-color: #d43f3a }
.btn-danger .badge { color: #d9534f; background-color: #fff }
.btn-link { color: #337ab7; font-weight: normal }
.btn-link,.btn-link:active,.btn-link.active,.btn-link[disabled],fieldset[disabled] .btn-link { background-color: transparent }
.btn-link,.btn-link:hover,.btn-link:focus,.btn-link:active { border-color: transparent }
.btn-link:hover,.btn-link:focus { color: #23527c; text-decoration: underline; background-color: transparent }
.btn-link[disabled]:hover,fieldset[disabled] .btn-link:hover,.btn-link[disabled]:focus,fieldset[disabled] .btn-link:focus { color: #777777; text-decoration: none }
.btn-lg,.btn-group-lg>.btn { padding: 10px 16px; font-size: 17px; line-height: 1.3333333 }
.btn-sm,.btn-group-sm>.btn { padding: 5px 10px; font-size: 12px; line-height: 1.5 }
.btn-xs,.btn-group-xs>.btn { padding: 1px 5px; font-size: 12px; line-height: 1.5 }
.btn-block { display: block; width: 100% }
.btn-block+.btn-block { margin-top: 5px }
input[type="submit"].btn-block,input[type="reset"].btn-block,input[type="button"].btn-block { width: 100% }
.fade { opacity: 0 }
.fade.in { opacity: 1 }
.collapse { display: none }
.collapse.in { display: block }
tr.collapse.in { display: table-row }
tbody.collapse.in { display: table-row-group }
.collapsing { position: relative; height: 0; overflow: hidden }
.caret { display: inline-block; width: 0; height: 0; margin-left: 2px; vertical-align: middle; border-top: 4px solid ; border-right: 4px solid transparent; border-left: 4px solid transparent }
.dropup,.dropdown { position: relative }
.dropdown-toggle:focus { outline: 0 }
.dropdown-menu { position: absolute; top: 100%; left: 0; z-index: 1000; display: none; float: left; min-width: 160px; padding: 5px 0; margin: 2px 0 0; list-style: none; font-size: 13px; text-align: left; background-color: #fff; border: 1px solid rgba(0, 0, 0, 0.15) }
.dropdown-menu.pull-right { right: 0; left: auto }
.dropdown-menu .divider { height: 1px; margin: 8px 0; overflow: hidden; background-color: #e5e5e5 }
.dropdown-menu>li>a { display: block; padding: 3px 20px; clear: both; font-weight: normal; line-height: 1.42857143; color: #333333; white-space: nowrap }
.dropdown-menu>li>a:hover,.dropdown-menu>li>a:focus { text-decoration: none; color: #262626; background-color: #f5f5f5 }
.dropdown-menu>.active>a,.dropdown-menu>.active>a:hover,.dropdown-menu>.active>a:focus { color: #fff; text-decoration: none; outline: 0; background-color: #337ab7 }
.dropdown-menu>.disabled>a,.dropdown-menu>.disabled>a:hover,.dropdown-menu>.disabled>a:focus { color: #777777 }
.dropdown-menu>.disabled>a:hover,.dropdown-menu>.disabled>a:focus { text-decoration: none; background-color: transparent; background-image: none; cursor: not-allowed }
.open>.dropdown-menu { display: block }
.open>a { outline: 0 }
.dropdown-menu-right { left: auto; right: 0 }
.dropdown-menu-left { left: 0; right: auto }
.dropdown-header { display: block; padding: 3px 20px; font-size: 12px; line-height: 1.42857143; color: #777777; white-space: nowrap }
.dropdown-backdrop { position: fixed; left: 0; right: 0; bottom: 0; top: 0; z-index: 990 }
.pull-right>.dropdown-menu { right: 0; left: auto }
.dropup .caret,.navbar-fixed-bottom .dropdown .caret { border-top: 0; border-bottom: 4px solid ; content: "" }
.dropup .dropdown-menu,.navbar-fixed-bottom .dropdown .dropdown-menu { top: auto; bottom: 100%; margin-bottom: 2px }
.btn-group,.btn-group-vertical { position: relative; display: inline-block; vertical-align: middle }
.btn-group>.btn,.btn-group-vertical>.btn { position: relative; float: left }
.btn-group>.btn:hover,.btn-group-vertical>.btn:hover,.btn-group>.btn:focus,.btn-group-vertical>.btn:focus,.btn-group>.btn:active,.btn-group-vertical>.btn:active,.btn-group>.btn.active,.btn-group-vertical>.btn.active { z-index: 2 }
.btn-group .btn+.btn,.btn-group .btn+.btn-group,.btn-group .btn-group+.btn,.btn-group .btn-group+.btn-group { margin-left: -1px }
.btn-toolbar { margin-left: -5px }
.btn-toolbar .btn,.btn-toolbar .btn-group,.btn-toolbar .input-group { float: left }
.btn-toolbar>.btn,.btn-toolbar>.btn-group,.btn-toolbar>.input-group { margin-left: 5px }
.btn-group>.btn:not(:first-child):not(:last-child):not(.dropdown-toggle) { }
.btn-group>.btn:first-child { margin-left: 0 }
.btn-group>.btn:first-child:not(:last-child):not(.dropdown-toggle) { }
.btn-group>.btn:last-child:not(:first-child),.btn-group>.dropdown-toggle:not(:first-child) { }
.btn-group>.btn-group { float: left }
.btn-group>.btn-group:not(:first-child):not(:last-child)>.btn { }
.btn-group>.btn-group:first-child:not(:last-child)>.btn:last-child,.btn-group>.btn-group:first-child:not(:last-child)>.dropdown-toggle { }
.btn-group>.btn-group:last-child:not(:first-child)>.btn:first-child { }
.btn-group .dropdown-toggle:active,.btn-group.open .dropdown-toggle { outline: 0 }
.btn-group>.btn+.dropdown-toggle { padding-left: 8px; padding-right: 8px }
.btn-group>.btn-lg+.dropdown-toggle { padding-left: 12px; padding-right: 12px }
.btn-group.open .dropdown-toggle { }
.btn-group.open .dropdown-toggle.btn-link { }
.btn .caret { margin-left: 0 }
.btn-lg .caret { border-width: 5px 5px 0; border-bottom-width: 0 }
.dropup .btn-lg .caret { border-width: 0 5px 5px }
.btn-group-vertical>.btn,.btn-group-vertical>.btn-group,.btn-group-vertical>.btn-group>.btn { display: block; float: none; width: 100%; max-width: 100% }
.btn-group-vertical>.btn-group>.btn { float: none }
.btn-group-vertical>.btn+.btn,.btn-group-vertical>.btn+.btn-group,.btn-group-vertical>.btn-group+.btn,.btn-group-vertical>.btn-group+.btn-group { margin-top: -1px; margin-left: 0 }
.btn-group-vertical>.btn:not(:first-child):not(:last-child) { }
.btn-group-vertical>.btn:first-child:not(:last-child) { }
.btn-group-vertical>.btn:last-child:not(:first-child) { }
.btn-group-vertical>.btn-group:not(:first-child):not(:last-child)>.btn { }
.btn-group-vertical>.btn-group:first-child:not(:last-child)>.btn:last-child,.btn-group-vertical>.btn-group:first-child:not(:last-child)>.dropdown-toggle { }
.btn-group-vertical>.btn-group:last-child:not(:first-child)>.btn:first-child { }
.btn-group-justified { display: table; width: 100%; table-layout: fixed; border-collapse: separate }
.btn-group-justified>.btn,.btn-group-justified>.btn-group { float: none; display: table-cell; width: 1% }
.btn-group-justified>.btn-group .btn { width: 100% }
.btn-group-justified>.btn-group .dropdown-menu { left: auto }
[data-toggle="buttons"]>.btn input[type="radio"],[data-toggle="buttons"]>.btn-group>.btn input[type="radio"],[data-toggle="buttons"]>.btn input[type="checkbox"],[data-toggle="buttons"]>.btn-group>.btn input[type="checkbox"] { position: absolute; clip: rect(0, 0, 0, 0) }
.input-group { position: relative; display: table; border-collapse: separate }
.input-group[class*="col-"] { float: none; padding-left: 0; padding-right: 0 }
.input-group .form-control { position: relative; z-index: 2; float: left; width: 100%; margin-bottom: 0 }
.input-group .form-control:focus { z-index: 3 }
.input-group-lg>.form-control,.input-group-lg>.input-group-addon,.input-group-lg>.input-group-btn>.btn { height: 45px; padding: 10px 16px; font-size: 17px; line-height: 1.3333333 }
select.input-group-lg>.form-control,select.input-group-lg>.input-group-addon,select.input-group-lg>.input-group-btn>.btn { height: 45px; line-height: 45px }
textarea.input-group-lg>.form-control,textarea.input-group-lg>.input-group-addon,textarea.input-group-lg>.input-group-btn>.btn,select[multiple].input-group-lg>.form-control,select[multiple].input-group-lg>.input-group-addon,select[multiple].input-group-lg>.input-group-btn>.btn { height: auto }
.input-group-sm>.form-control,.input-group-sm>.input-group-addon,.input-group-sm>.input-group-btn>.btn { height: 30px; padding: 5px 10px; font-size: 12px; line-height: 1.5 }
select.input-group-sm>.form-control,select.input-group-sm>.input-group-addon,select.input-group-sm>.input-group-btn>.btn { height: 30px; line-height: 30px }
textarea.input-group-sm>.form-control,textarea.input-group-sm>.input-group-addon,textarea.input-group-sm>.input-group-btn>.btn,select[multiple].input-group-sm>.form-control,select[multiple].input-group-sm>.input-group-addon,select[multiple].input-group-sm>.input-group-btn>.btn { height: auto }
.input-group-addon,.input-group-btn,.input-group .form-control { display: table-cell }
.input-group-addon:not(:first-child):not(:last-child),.input-group-btn:not(:first-child):not(:last-child),.input-group .form-control:not(:first-child):not(:last-child) { }
.input-group-addon,.input-group-btn { width: 1%; white-space: nowrap; vertical-align: middle }
.input-group-addon { padding: 6px 12px; font-size: 13px; font-weight: normal; line-height: 1; color: #555555; text-align: center; background-color: #eeeeee; border: 1px solid #ccc }
.input-group-addon.input-sm { padding: 5px 10px; font-size: 12px }
.input-group-addon.input-lg { padding: 10px 16px; font-size: 17px }
.input-group-addon input[type="radio"],.input-group-addon input[type="checkbox"] { margin-top: 0 }
.input-group .form-control:first-child,.input-group-addon:first-child,.input-group-btn:first-child>.btn,.input-group-btn:first-child>.btn-group>.btn,.input-group-btn:first-child>.dropdown-toggle,.input-group-btn:last-child>.btn:not(:last-child):not(.dropdown-toggle),.input-group-btn:last-child>.btn-group:not(:last-child)>.btn { }
.input-group-addon:first-child { border-right: 0 }
.input-group .form-control:last-child,.input-group-addon:last-child,.input-group-btn:last-child>.btn,.input-group-btn:last-child>.btn-group>.btn,.input-group-btn:last-child>.dropdown-toggle,.input-group-btn:first-child>.btn:not(:first-child),.input-group-btn:first-child>.btn-group:not(:first-child)>.btn { }
.input-group-addon:last-child { border-left: 0 }
.input-group-btn { position: relative; font-size: 0; white-space: nowrap }
.input-group-btn>.btn { position: relative }
.input-group-btn>.btn+.btn { margin-left: -1px }
.input-group-btn>.btn:hover,.input-group-btn>.btn:focus,.input-group-btn>.btn:active { z-index: 2 }
.input-group-btn:first-child>.btn,.input-group-btn:first-child>.btn-group { margin-right: -1px }
.input-group-btn:last-child>.btn,.input-group-btn:last-child>.btn-group { z-index: 2; margin-left: -1px }
.nav { margin-bottom: 0; padding-left: 0; list-style: none }
.nav>li { position: relative; display: block }
.nav>li>a { position: relative; display: block; padding: 10px 15px }
.nav>li>a:hover,.nav>li>a:focus { text-decoration: none; background-color: #eeeeee }
.nav>li.disabled>a { color: #777777 }
.nav>li.disabled>a:hover,.nav>li.disabled>a:focus { color: #777777; text-decoration: none; background-color: transparent; cursor: not-allowed }
.nav .open>a,.nav .open>a:hover,.nav .open>a:focus { background-color: #eeeeee; border-color: #337ab7 }
.nav .nav-divider { height: 1px; margin: 8px 0; overflow: hidden; background-color: #e5e5e5 }
.nav>li>a>img { max-width: none }
.nav-tabs { border-bottom: 1px solid #ddd }
.nav-tabs>li { float: left; margin-bottom: -1px }
.nav-tabs>li>a { margin-right: 2px; line-height: 1.42857143; border: 1px solid transparent }
.nav-tabs>li>a:hover { border-color: #eeeeee #eeeeee #ddd }
.nav-tabs>li.active>a,.nav-tabs>li.active>a:hover,.nav-tabs>li.active>a:focus { color: #555555; background-color: #fff; border: 1px solid #ddd; border-bottom-color: transparent; cursor: default }
.nav-tabs.nav-justified { width: 100%; border-bottom: 0 }
.nav-tabs.nav-justified>li { float: none }
.nav-tabs.nav-justified>li>a { text-align: center; margin-bottom: 5px }
.nav-tabs.nav-justified>.dropdown .dropdown-menu { top: auto; left: auto }
.nav-tabs.nav-justified>li>a { margin-right: 0 }
.nav-tabs.nav-justified>.active>a,.nav-tabs.nav-justified>.active>a:hover,.nav-tabs.nav-justified>.active>a:focus { border: 1px solid #ddd }
.nav-pills>li { float: left }
.nav-pills>li>a { }
.nav-pills>li+li { margin-left: 2px }
.nav-pills>li.active>a,.nav-pills>li.active>a:hover,.nav-pills>li.active>a:focus { color: #fff; background-color: #337ab7 }
.nav-stacked>li { float: none }
.nav-stacked>li+li { margin-top: 2px; margin-left: 0 }
.nav-justified { width: 100% }
.nav-justified>li { float: none }
.nav-justified>li>a { text-align: center; margin-bottom: 5px }
.nav-justified>.dropdown .dropdown-menu { top: auto; left: auto }
.nav-tabs-justified { border-bottom: 0 }
.nav-tabs-justified>li>a { margin-right: 0 }
.nav-tabs-justified>.active>a,.nav-tabs-justified>.active>a:hover,.nav-tabs-justified>.active>a:focus { border: 1px solid #ddd }
.tab-content>.tab-pane { display: none }
.tab-content>.active { display: block }
.nav-tabs .dropdown-menu { margin-top: -1px }
.navbar { position: relative; min-height: 30px; margin-bottom: 18px; border: 1px solid transparent }
.navbar-collapse { padding-right: 0px; padding-left: 0px; border-top: 1px solid transparent }
.navbar-collapse.in { }
.navbar-fixed-top .navbar-collapse,.navbar-fixed-bottom .navbar-collapse { max-height: 340px }
.container>.navbar-header,.container-fluid>.navbar-header,.container>.navbar-collapse,.container-fluid>.navbar-collapse { margin-right: 0px; margin-left: 0px }
.navbar-static-top { z-index: 1000; border-width: 0 0 1px }
.navbar-fixed-top,.navbar-fixed-bottom { position: fixed; right: 0; left: 0; z-index: 1030 }
.navbar-fixed-top { top: 0; border-width: 0 0 1px }
.navbar-fixed-bottom { bottom: 0; margin-bottom: 0; border-width: 1px 0 0 }
.navbar-brand { float: left; padding: 6px 0px; font-size: 17px; line-height: 18px; height: 30px }
.navbar-brand:hover,.navbar-brand:focus { text-decoration: none }
.navbar-brand>img { display: block }
.navbar-toggle { position: relative; float: right; margin-right: 0px; padding: 9px 10px; margin-top: -2px; margin-bottom: -2px; background-color: transparent; background-image: none; border: 1px solid transparent }
.navbar-toggle:focus { outline: 0 }
.navbar-toggle .icon-bar { display: block; width: 22px; height: 2px }
.navbar-toggle .icon-bar+.icon-bar { margin-top: 4px }
.navbar-nav { margin: 3px 0px }
.navbar-nav>li>a { padding-top: 10px; padding-bottom: 10px; line-height: 18px }
.navbar-form { margin-left: 0px; margin-right: 0px; padding: 10px 0px; border-top: 1px solid transparent; border-bottom: 1px solid transparent; margin-top: -1px; margin-bottom: -1px }
.navbar-nav>li>.dropdown-menu { margin-top: 0 }
.navbar-fixed-bottom .navbar-nav>li>.dropdown-menu { margin-bottom: 0 }
.navbar-btn { margin-top: -1px; margin-bottom: -1px }
.navbar-btn.btn-sm { margin-top: 0px; margin-bottom: 0px }
.navbar-btn.btn-xs { margin-top: 4px; margin-bottom: 4px }
.navbar-text { margin-top: 6px; margin-bottom: 6px }
.navbar-default { background-color: #f8f8f8; border-color: #e7e7e7 }
.navbar-default .navbar-brand { color: #777 }
.navbar-default .navbar-brand:hover,.navbar-default .navbar-brand:focus { color: #5e5e5e; background-color: transparent }
.navbar-default .navbar-text { color: #777 }
.navbar-default .navbar-nav>li>a { color: #777 }
.navbar-default .navbar-nav>li>a:hover,.navbar-default .navbar-nav>li>a:focus { color: #333; background-color: transparent }
.navbar-default .navbar-nav>.active>a,.navbar-default .navbar-nav>.active>a:hover,.navbar-default .navbar-nav>.active>a:focus { color: #555; background-color: #e7e7e7 }
.navbar-default .navbar-nav>.disabled>a,.navbar-default .navbar-nav>.disabled>a:hover,.navbar-default .navbar-nav>.disabled>a:focus { color: #ccc; background-color: transparent }
.navbar-default .navbar-toggle { border-color: #ddd }
.navbar-default .navbar-toggle:hover,.navbar-default .navbar-toggle:focus { background-color: #ddd }
.navbar-default .navbar-toggle .icon-bar { background-color: #888 }
.navbar-default .navbar-collapse,.navbar-default .navbar-form { border-color: #e7e7e7 }
.navbar-default .navbar-nav>.open>a,.navbar-default .navbar-nav>.open>a:hover,.navbar-default .navbar-nav>.open>a:focus { background-color: #e7e7e7; color: #555 }
.navbar-default .navbar-link { color: #777 }
.navbar-default .navbar-link:hover { color: #333 }
.navbar-default .btn-link { color: #777 }
.navbar-default .btn-link:hover,.navbar-default .btn-link:focus { color: #333 }
.navbar-default .btn-link[disabled]:hover,fieldset[disabled] .navbar-default .btn-link:hover,.navbar-default .btn-link[disabled]:focus,fieldset[disabled] .navbar-default .btn-link:focus { color: #ccc }
.navbar-inverse { background-color: #222; border-color: #080808 }
.navbar-inverse .navbar-brand { color: #9d9d9d }
.navbar-inverse .navbar-brand:hover,.navbar-inverse .navbar-brand:focus { color: #fff; background-color: transparent }
.navbar-inverse .navbar-text { color: #9d9d9d }
.navbar-inverse .navbar-nav>li>a { color: #9d9d9d }
.navbar-inverse .navbar-nav>li>a:hover,.navbar-inverse .navbar-nav>li>a:focus { color: #fff; background-color: transparent }
.navbar-inverse .navbar-nav>.active>a,.navbar-inverse .navbar-nav>.active>a:hover,.navbar-inverse .navbar-nav>.active>a:focus { color: #fff; background-color: #080808 }
.navbar-inverse .navbar-nav>.disabled>a,.navbar-inverse .navbar-nav>.disabled>a:hover,.navbar-inverse .navbar-nav>.disabled>a:focus { color: #444; background-color: transparent }
.navbar-inverse .navbar-toggle { border-color: #333 }
.navbar-inverse .navbar-toggle:hover,.navbar-inverse .navbar-toggle:focus { background-color: #333 }
.navbar-inverse .navbar-toggle .icon-bar { background-color: #fff }
.navbar-inverse .navbar-collapse,.navbar-inverse .navbar-form { border-color: #101010 }
.navbar-inverse .navbar-nav>.open>a,.navbar-inverse .navbar-nav>.open>a:hover,.navbar-inverse .navbar-nav>.open>a:focus { background-color: #080808; color: #fff }
.navbar-inverse .navbar-link { color: #9d9d9d }
.navbar-inverse .navbar-link:hover { color: #fff }
.navbar-inverse .btn-link { color: #9d9d9d }
.navbar-inverse .btn-link:hover,.navbar-inverse .btn-link:focus { color: #fff }
.navbar-inverse .btn-link[disabled]:hover,fieldset[disabled] .navbar-inverse .btn-link:hover,.navbar-inverse .btn-link[disabled]:focus,fieldset[disabled] .navbar-inverse .btn-link:focus { color: #444 }
.breadcrumb { padding: 8px 15px; margin-bottom: 18px; list-style: none; background-color: #f5f5f5 }
.breadcrumb>li { display: inline-block }
.breadcrumb>li+li::before { content: "/?"; padding: 0 5px; color: #5e5e5e }
.breadcrumb>.active { color: #777777 }
.pagination { display: inline-block; padding-left: 0; margin: 18px 0 }
.pagination>li { display: inline }
.pagination>li>a,.pagination>li>span { position: relative; float: left; padding: 6px 12px; line-height: 1.42857143; text-decoration: none; color: #337ab7; background-color: #fff; border: 1px solid #ddd; margin-left: -1px }
.pagination>li:first-child>a,.pagination>li:first-child>span { margin-left: 0 }
.pagination>li:last-child>a,.pagination>li:last-child>span { }
.pagination>li>a:hover,.pagination>li>span:hover,.pagination>li>a:focus,.pagination>li>span:focus { z-index: 2; color: #23527c; background-color: #eeeeee; border-color: #ddd }
.pagination>.active>a,.pagination>.active>span,.pagination>.active>a:hover,.pagination>.active>span:hover,.pagination>.active>a:focus,.pagination>.active>span:focus { z-index: 3; color: #fff; background-color: #337ab7; border-color: #337ab7; cursor: default }
.pagination>.disabled>span,.pagination>.disabled>span:hover,.pagination>.disabled>span:focus,.pagination>.disabled>a,.pagination>.disabled>a:hover,.pagination>.disabled>a:focus { color: #777777; background-color: #fff; border-color: #ddd; cursor: not-allowed }
.pagination-lg>li>a,.pagination-lg>li>span { padding: 10px 16px; font-size: 17px; line-height: 1.3333333 }
.pagination-lg>li:first-child>a,.pagination-lg>li:first-child>span { }
.pagination-lg>li:last-child>a,.pagination-lg>li:last-child>span { }
.pagination-sm>li>a,.pagination-sm>li>span { padding: 5px 10px; font-size: 12px; line-height: 1.5 }
.pagination-sm>li:first-child>a,.pagination-sm>li:first-child>span { }
.pagination-sm>li:last-child>a,.pagination-sm>li:last-child>span { }
.pager { padding-left: 0; margin: 18px 0; list-style: none; text-align: center }
.pager li { display: inline }
.pager li>a,.pager li>span { display: inline-block; padding: 5px 14px; background-color: #fff; border: 1px solid #ddd }
.pager li>a:hover,.pager li>a:focus { text-decoration: none; background-color: #eeeeee }
.pager .next>a,.pager .next>span { float: right }
.pager .previous>a,.pager .previous>span { float: left }
.pager .disabled>a,.pager .disabled>a:hover,.pager .disabled>a:focus,.pager .disabled>span { color: #777777; background-color: #fff; cursor: not-allowed }
.label { display: inline; padding: .2em .6em .3em; font-size: 75%; font-weight: bold; line-height: 1; color: #fff; text-align: center; white-space: nowrap; vertical-align: baseline }
a.label:hover,a.label:focus { color: #fff; text-decoration: none; cursor: pointer }
.label:empty { display: none }
.btn .label { position: relative; top: -1px }
.label-default { background-color: #777777 }
.label-default[href]:hover,.label-default[href]:focus { background-color: #5e5e5e }
.label-primary { background-color: #337ab7 }
.label-primary[href]:hover,.label-primary[href]:focus { background-color: #286090 }
.label-success { background-color: #5cb85c }
.label-success[href]:hover,.label-success[href]:focus { background-color: #449d44 }
.label-info { background-color: #5bc0de }
.label-info[href]:hover,.label-info[href]:focus { background-color: #31b0d5 }
.label-warning { background-color: #f0ad4e }
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.label-danger { background-color: #d9534f }
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.modal-footer .btn+.btn { margin-left: 5px; margin-bottom: 0 }
.modal-footer .btn-group .btn+.btn { margin-left: -1px }
.modal-footer .btn-block+.btn-block { margin-left: 0 }
.modal-scrollbar-measure { position: absolute; top: -9999px; width: 50px; height: 50px; overflow: scroll }
.tooltip { position: absolute; z-index: 1070; display: block; font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; font-style: normal; font-weight: normal; letter-spacing: normal; line-height: 1.42857143; text-align: start; text-decoration: none; text-transform: none; white-space: normal; word-spacing: normal; font-size: 12px; opacity: 0 }
.tooltip.in { opacity: 0.9 }
.tooltip.top { margin-top: -3px; padding: 5px 0 }
.tooltip.right { margin-left: 3px; padding: 0 5px }
.tooltip.bottom { margin-top: 3px; padding: 5px 0 }
.tooltip.left { margin-left: -3px; padding: 0 5px }
.tooltip-inner { max-width: 200px; padding: 3px 8px; color: #fff; text-align: center; background-color: #000 }
.tooltip-arrow { position: absolute; width: 0; height: 0; border-color: transparent; border-style: solid }
.tooltip.top .tooltip-arrow { bottom: 0; left: 50%; margin-left: -5px; border-width: 5px 5px 0; border-top-color: #000 }
.tooltip.top-left .tooltip-arrow { bottom: 0; right: 5px; margin-bottom: -5px; border-width: 5px 5px 0; border-top-color: #000 }
.tooltip.top-right .tooltip-arrow { bottom: 0; left: 5px; margin-bottom: -5px; border-width: 5px 5px 0; border-top-color: #000 }
.tooltip.right .tooltip-arrow { top: 50%; left: 0; margin-top: -5px; border-width: 5px 5px 5px 0; border-right-color: #000 }
.tooltip.left .tooltip-arrow { top: 50%; right: 0; margin-top: -5px; border-width: 5px 0 5px 5px; border-left-color: #000 }
.tooltip.bottom .tooltip-arrow { top: 0; left: 50%; margin-left: -5px; border-width: 0 5px 5px; border-bottom-color: #000 }
.tooltip.bottom-left .tooltip-arrow { top: 0; right: 5px; margin-top: -5px; border-width: 0 5px 5px; border-bottom-color: #000 }
.tooltip.bottom-right .tooltip-arrow { top: 0; left: 5px; margin-top: -5px; border-width: 0 5px 5px; border-bottom-color: #000 }
.popover { position: absolute; top: 0; left: 0; z-index: 1060; display: none; max-width: 276px; padding: 1px; font-family: "Helvetica Neue", Helvetica, Arial, sans-serif; font-style: normal; font-weight: normal; letter-spacing: normal; line-height: 1.42857143; text-align: start; text-decoration: none; text-transform: none; white-space: normal; word-spacing: normal; font-size: 13px; background-color: #fff; border: 1px solid rgba(0, 0, 0, 0.2) }
.popover.top { margin-top: -10px }
.popover.right { margin-left: 10px }
.popover.bottom { margin-top: 10px }
.popover.left { margin-left: -10px }
.popover-title { margin: 0; padding: 8px 14px; font-size: 13px; background-color: #f7f7f7; border-bottom: 1px solid #ebebeb }
.popover-content { padding: 9px 14px }
.popover>.arrow,.popover>.arrow::after { position: absolute; display: block; width: 0; height: 0; border-color: transparent; border-style: solid }
.popover>.arrow { border-width: 11px }
.popover>.arrow::after { border-width: 10px; content: "" }
.popover.top>.arrow { left: 50%; margin-left: -11px; border-bottom-width: 0; border-top-color: rgba(0, 0, 0, 0.25); bottom: -11px }
.popover.top>.arrow::after { content: " "; bottom: 1px; margin-left: -10px; border-bottom-width: 0; border-top-color: #fff }
.popover.right>.arrow { top: 50%; left: -11px; margin-top: -11px; border-left-width: 0; border-right-color: rgba(0, 0, 0, 0.25) }
.popover.right>.arrow::after { content: " "; left: 1px; bottom: -10px; border-left-width: 0; border-right-color: #fff }
.popover.bottom>.arrow { left: 50%; margin-left: -11px; border-top-width: 0; border-bottom-color: rgba(0, 0, 0, 0.25); top: -11px }
.popover.bottom>.arrow::after { content: " "; top: 1px; margin-left: -10px; border-top-width: 0; border-bottom-color: #fff }
.popover.left>.arrow { top: 50%; right: -11px; margin-top: -11px; border-right-width: 0; border-left-color: rgba(0, 0, 0, 0.25) }
.popover.left>.arrow::after { content: " "; right: 1px; border-right-width: 0; border-left-color: #fff; bottom: -10px }
.carousel { position: relative }
.carousel-inner { position: relative; overflow: hidden; width: 100% }
.carousel-inner>.item { display: none; position: relative }
.carousel-inner>.item>img,.carousel-inner>.item>a>img { line-height: 1 }
.carousel-inner>.active,.carousel-inner>.next,.carousel-inner>.prev { display: block }
.carousel-inner>.active { left: 0 }
.carousel-inner>.next,.carousel-inner>.prev { position: absolute; top: 0; width: 100% }
.carousel-inner>.next { left: 100% }
.carousel-inner>.prev { left: -100% }
.carousel-inner>.next.left,.carousel-inner>.prev.right { left: 0 }
.carousel-inner>.active.left { left: -100% }
.carousel-inner>.active.right { left: 100% }
.carousel-control { position: absolute; top: 0; left: 0; bottom: 0; width: 15%; opacity: 0.5; font-size: 20px; color: #fff; text-align: center; background-color: rgba(0, 0, 0, 0) }
.carousel-control.left { background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%); background-repeat: repeat-x }
.carousel-control.right { left: auto; right: 0; background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%); background-repeat: repeat-x }
.carousel-control:hover,.carousel-control:focus { outline: 0; color: #fff; text-decoration: none; opacity: 0.9 }
.carousel-control .icon-prev,.carousel-control .icon-next,.carousel-control .glyphicon-chevron-left,.carousel-control .glyphicon-chevron-right { position: absolute; top: 50%; margin-top: -10px; z-index: 5; display: inline-block }
.carousel-control .icon-prev,.carousel-control .glyphicon-chevron-left { left: 50%; margin-left: -10px }
.carousel-control .icon-next,.carousel-control .glyphicon-chevron-right { right: 50%; margin-right: -10px }
.carousel-control .icon-prev,.carousel-control .icon-next { width: 20px; height: 20px; line-height: 1; font-family: serif }
.carousel-control .icon-prev::before { content: "?" }
.carousel-control .icon-next::before { content: "?" }
.carousel-indicators { position: absolute; bottom: 10px; left: 50%; z-index: 15; width: 60%; margin-left: -30%; padding-left: 0; list-style: none; text-align: center }
.carousel-indicators li { display: inline-block; width: 10px; height: 10px; margin: 1px; text-indent: -999px; border: 1px solid #fff; cursor: pointer; background-color: rgba(0, 0, 0, 0) }
.carousel-indicators .active { margin: 0; width: 12px; height: 12px; background-color: #fff }
.carousel-caption { position: absolute; left: 15%; right: 15%; bottom: 20px; z-index: 10; padding-top: 20px; padding-bottom: 20px; color: #fff; text-align: center }
.carousel-caption .btn { }
.clearfix::before,.clearfix::after,.dl-horizontal dd::before,.dl-horizontal dd::after,.container::before,.container::after,.container-fluid::before,.container-fluid::after,.row::before,.row::after,.form-horizontal .form-group::before,.form-horizontal .form-group::after,.btn-toolbar::before,.btn-toolbar::after,.btn-group-vertical>.btn-group::before,.btn-group-vertical>.btn-group::after,.nav::before,.nav::after,.navbar::before,.navbar::after,.navbar-header::before,.navbar-header::after,.navbar-collapse::before,.navbar-collapse::after,.pager::before,.pager::after,.panel-body::before,.panel-body::after,.modal-header::before,.modal-header::after,.modal-footer::before,.modal-footer::after,.item_buttons::before,.item_buttons::after { content: " "; display: table }
.clearfix::after,.dl-horizontal dd::after,.container::after,.container-fluid::after,.row::after,.form-horizontal .form-group::after,.btn-toolbar::after,.btn-group-vertical>.btn-group::after,.nav::after,.navbar::after,.navbar-header::after,.navbar-collapse::after,.pager::after,.panel-body::after,.modal-header::after,.modal-footer::after,.item_buttons::after { clear: both }
.center-block { display: block; margin-left: auto; margin-right: auto }
.pull-right { float: right !important }
.pull-left { float: left !important }
.hide { display: none !important }
.show { display: block !important }
.invisible { visibility: hidden }
.text-hide { font: 0/0 a; color: transparent; background-color: transparent; border: 0 }
.hidden { display: none !important }
.affix { position: fixed }
.visible-xs,.visible-sm,.visible-md,.visible-lg { display: none !important }
.visible-xs-block,.visible-xs-inline,.visible-xs-inline-block,.visible-sm-block,.visible-sm-inline,.visible-sm-inline-block,.visible-md-block,.visible-md-inline,.visible-md-inline-block,.visible-lg-block,.visible-lg-inline,.visible-lg-inline-block { display: none !important }
.visible-print { display: none !important }
.visible-print-block { display: none !important }
.visible-print-inline { display: none !important }
.visible-print-inline-block { display: none !important }
.fa { display: inline-block; font: normal normal normal 14px/1 FontAwesome; font-size: inherit }
.fa-lg { font-size: 1.33333333em; line-height: 0.75em; vertical-align: -15% }
.fa-2x { font-size: 2em }
.fa-3x { font-size: 3em }
.fa-4x { font-size: 4em }
.fa-5x { font-size: 5em }
.fa-fw { width: 1.28571429em; text-align: center }
.fa-ul { padding-left: 0; margin-left: 2.14285714em; list-style-type: none }
.fa-ul>li { position: relative }
.fa-li { position: absolute; left: -2.14285714em; width: 2.14285714em; top: 0.14285714em; text-align: center }
.fa-li.fa-lg { left: -1.85714286em }
.fa-border { padding: .2em .25em .15em; border: solid 0.08em #eee }
.pull-right { float: right }
.pull-left { float: left }
.fa.pull-left { margin-right: .3em }
.fa.pull-right { margin-left: .3em }
.fa-spin { }
.fa-rotate-90 { }
.fa-rotate-180 { }
.fa-rotate-270 { }
.fa-flip-horizontal { }
.fa-flip-vertical { }
:root .fa-rotate-90,:root .fa-rotate-180,:root .fa-rotate-270,:root .fa-flip-horizontal,:root .fa-flip-vertical { }
.fa-stack { position: relative; display: inline-block; width: 2em; height: 2em; line-height: 2em; vertical-align: middle }
.fa-stack-1x,.fa-stack-2x { position: absolute; left: 0; width: 100%; text-align: center }
.fa-stack-1x { line-height: inherit }
.fa-stack-2x { font-size: 2em }
.fa-inverse { color: #fff }
.fa-glass::before { content: "?" }
.fa-music::before { content: "?" }
.fa-search::before { content: "?" }
.fa-envelope-o::before { content: "?" }
.fa-heart::before { content: "?" }
.fa-star::before { content: "?" }
.fa-star-o::before { content: "?" }
.fa-user::before { content: "?" }
.fa-film::before { content: "?" }
.fa-th-large::before { content: "?" }
.fa-th::before { content: "?" }
.fa-th-list::before { content: "?" }
.fa-check::before { content: "?" }
.fa-remove::before,.fa-close::before,.fa-times::before { content: "?" }
.fa-search-plus::before { content: "?" }
.fa-search-minus::before { content: "?" }
.fa-power-off::before { content: "?" }
.fa-signal::before { content: "?" }
.fa-gear::before,.fa-cog::before { content: "?" }
.fa-trash-o::before { content: "?" }
.fa-home::before { content: "?" }
.fa-file-o::before { content: "?" }
.fa-clock-o::before { content: "?" }
.fa-road::before { content: "?" }
.fa-download::before { content: "?" }
.fa-arrow-circle-o-down::before { content: "?" }
.fa-arrow-circle-o-up::before { content: "?" }
.fa-inbox::before { content: "?" }
.fa-play-circle-o::before { content: "?" }
.fa-rotate-right::before,.fa-repeat::before { content: "?" }
.fa-refresh::before { content: "?" }
.fa-list-alt::before { content: "?" }
.fa-lock::before { content: "?" }
.fa-flag::before { content: "?" }
.fa-headphones::before { content: "?" }
.fa-volume-off::before { content: "?" }
.fa-volume-down::before { content: "?" }
.fa-volume-up::before { content: "?" }
.fa-qrcode::before { content: "?" }
.fa-barcode::before { content: "?" }
.fa-tag::before { content: "?" }
.fa-tags::before { content: "?" }
.fa-book::before { content: "?" }
.fa-bookmark::before { content: "?" }
.fa-print::before { content: "?" }
.fa-camera::before { content: "?" }
.fa-font::before { content: "?" }
.fa-bold::before { content: "?" }
.fa-italic::before { content: "?" }
.fa-text-height::before { content: "?" }
.fa-text-width::before { content: "?" }
.fa-align-left::before { content: "?" }
.fa-align-center::before { content: "?" }
.fa-align-right::before { content: "?" }
.fa-align-justify::before { content: "?" }
.fa-list::before { content: "?" }
.fa-dedent::before,.fa-outdent::before { content: "?" }
.fa-indent::before { content: "?" }
.fa-video-camera::before { content: "?" }
.fa-photo::before,.fa-image::before,.fa-picture-o::before { content: "?" }
.fa-pencil::before { content: "?" }
.fa-map-marker::before { content: "?" }
.fa-adjust::before { content: "?" }
.fa-tint::before { content: "?" }
.fa-edit::before,.fa-pencil-square-o::before { content: "?" }
.fa-share-square-o::before { content: "?" }
.fa-check-square-o::before { content: "?" }
.fa-arrows::before { content: "?" }
.fa-step-backward::before { content: "?" }
.fa-fast-backward::before { content: "?" }
.fa-backward::before { content: "?" }
.fa-play::before { content: "?" }
.fa-pause::before { content: "?" }
.fa-stop::before { content: "?" }
.fa-forward::before { content: "?" }
.fa-fast-forward::before { content: "?" }
.fa-step-forward::before { content: "?" }
.fa-eject::before { content: "?" }
.fa-chevron-left::before { content: "?" }
.fa-chevron-right::before { content: "?" }
.fa-plus-circle::before { content: "?" }
.fa-minus-circle::before { content: "?" }
.fa-times-circle::before { content: "?" }
.fa-check-circle::before { content: "?" }
.fa-question-circle::before { content: "?" }
.fa-info-circle::before { content: "?" }
.fa-crosshairs::before { content: "?" }
.fa-times-circle-o::before { content: "?" }
.fa-check-circle-o::before { content: "?" }
.fa-ban::before { content: "?" }
.fa-arrow-left::before { content: "?" }
.fa-arrow-right::before { content: "?" }
.fa-arrow-up::before { content: "?" }
.fa-arrow-down::before { content: "?" }
.fa-mail-forward::before,.fa-share::before { content: "?" }
.fa-expand::before { content: "?" }
.fa-compress::before { content: "?" }
.fa-plus::before { content: "?" }
.fa-minus::before { content: "?" }
.fa-asterisk::before { content: "?" }
.fa-exclamation-circle::before { content: "?" }
.fa-gift::before { content: "?" }
.fa-leaf::before { content: "?" }
.fa-fire::before { content: "?" }
.fa-eye::before { content: "?" }
.fa-eye-slash::before { content: "?" }
.fa-warning::before,.fa-exclamation-triangle::before { content: "?" }
.fa-plane::before { content: "?" }
.fa-calendar::before { content: "?" }
.fa-random::before { content: "?" }
.fa-comment::before { content: "?" }
.fa-magnet::before { content: "?" }
.fa-chevron-up::before { content: "?" }
.fa-chevron-down::before { content: "?" }
.fa-retweet::before { content: "?" }
.fa-shopping-cart::before { content: "?" }
.fa-folder::before { content: "?" }
.fa-folder-open::before { content: "?" }
.fa-arrows-v::before { content: "?" }
.fa-arrows-h::before { content: "?" }
.fa-bar-chart-o::before,.fa-bar-chart::before { content: "?" }
.fa-twitter-square::before { content: "?" }
.fa-facebook-square::before { content: "?" }
.fa-camera-retro::before { content: "?" }
.fa-key::before { content: "?" }
.fa-gears::before,.fa-cogs::before { content: "?" }
.fa-comments::before { content: "?" }
.fa-thumbs-o-up::before { content: "?" }
.fa-thumbs-o-down::before { content: "?" }
.fa-star-half::before { content: "?" }
.fa-heart-o::before { content: "?" }
.fa-sign-out::before { content: "?" }
.fa-linkedin-square::before { content: "?" }
.fa-thumb-tack::before { content: "?" }
.fa-external-link::before { content: "?" }
.fa-sign-in::before { content: "?" }
.fa-trophy::before { content: "?" }
.fa-github-square::before { content: "?" }
.fa-upload::before { content: "?" }
.fa-lemon-o::before { content: "?" }
.fa-phone::before { content: "?" }
.fa-square-o::before { content: "?" }
.fa-bookmark-o::before { content: "?" }
.fa-phone-square::before { content: "?" }
.fa-twitter::before { content: "?" }
.fa-facebook::before { content: "?" }
.fa-github::before { content: "?" }
.fa-unlock::before { content: "?" }
.fa-credit-card::before { content: "?" }
.fa-rss::before { content: "?" }
.fa-hdd-o::before { content: "?" }
.fa-bullhorn::before { content: "?" }
.fa-bell::before { content: "?" }
.fa-certificate::before { content: "?" }
.fa-hand-o-right::before { content: "?" }
.fa-hand-o-left::before { content: "?" }
.fa-hand-o-up::before { content: "?" }
.fa-hand-o-down::before { content: "?" }
.fa-arrow-circle-left::before { content: "?" }
.fa-arrow-circle-right::before { content: "?" }
.fa-arrow-circle-up::before { content: "?" }
.fa-arrow-circle-down::before { content: "?" }
.fa-globe::before { content: "?" }
.fa-wrench::before { content: "?" }
.fa-tasks::before { content: "?" }
.fa-filter::before { content: "?" }
.fa-briefcase::before { content: "?" }
.fa-arrows-alt::before { content: "?" }
.fa-group::before,.fa-users::before { content: "?" }
.fa-chain::before,.fa-link::before { content: "?" }
.fa-cloud::before { content: "?" }
.fa-flask::before { content: "?" }
.fa-cut::before,.fa-scissors::before { content: "?" }
.fa-copy::before,.fa-files-o::before { content: "?" }
.fa-paperclip::before { content: "?" }
.fa-save::before,.fa-floppy-o::before { content: "?" }
.fa-square::before { content: "?" }
.fa-navicon::before,.fa-reorder::before,.fa-bars::before { content: "?" }
.fa-list-ul::before { content: "?" }
.fa-list-ol::before { content: "?" }
.fa-strikethrough::before { content: "?" }
.fa-underline::before { content: "?" }
.fa-table::before { content: "?" }
.fa-magic::before { content: "?" }
.fa-truck::before { content: "?" }
.fa-pinterest::before { content: "?" }
.fa-pinterest-square::before { content: "?" }
.fa-google-plus-square::before { content: "?" }
.fa-google-plus::before { content: "?" }
.fa-money::before { content: "?" }
.fa-caret-down::before { content: "?" }
.fa-caret-up::before { content: "?" }
.fa-caret-left::before { content: "?" }
.fa-caret-right::before { content: "?" }
.fa-columns::before { content: "?" }
.fa-unsorted::before,.fa-sort::before { content: "?" }
.fa-sort-down::before,.fa-sort-desc::before { content: "?" }
.fa-sort-up::before,.fa-sort-asc::before { content: "?" }
.fa-envelope::before { content: "?" }
.fa-linkedin::before { content: "?" }
.fa-rotate-left::before,.fa-undo::before { content: "?" }
.fa-legal::before,.fa-gavel::before { content: "?" }
.fa-dashboard::before,.fa-tachometer::before { content: "?" }
.fa-comment-o::before { content: "?" }
.fa-comments-o::before { content: "?" }
.fa-flash::before,.fa-bolt::before { content: "?" }
.fa-sitemap::before { content: "?" }
.fa-umbrella::before { content: "?" }
.fa-paste::before,.fa-clipboard::before { content: "?" }
.fa-lightbulb-o::before { content: "?" }
.fa-exchange::before { content: "?" }
.fa-cloud-download::before { content: "?" }
.fa-cloud-upload::before { content: "?" }
.fa-user-md::before { content: "?" }
.fa-stethoscope::before { content: "?" }
.fa-suitcase::before { content: "?" }
.fa-bell-o::before { content: "?" }
.fa-coffee::before { content: "?" }
.fa-cutlery::before { content: "?" }
.fa-file-text-o::before { content: "?" }
.fa-building-o::before { content: "?" }
.fa-hospital-o::before { content: "?" }
.fa-ambulance::before { content: "?" }
.fa-medkit::before { content: "?" }
.fa-fighter-jet::before { content: "?" }
.fa-beer::before { content: "?" }
.fa-h-square::before { content: "?" }
.fa-plus-square::before { content: "?" }
.fa-angle-double-left::before { content: "?" }
.fa-angle-double-right::before { content: "?" }
.fa-angle-double-up::before { content: "?" }
.fa-angle-double-down::before { content: "?" }
.fa-angle-left::before { content: "?" }
.fa-angle-right::before { content: "?" }
.fa-angle-up::before { content: "?" }
.fa-angle-down::before { content: "?" }
.fa-desktop::before { content: "?" }
.fa-laptop::before { content: "?" }
.fa-tablet::before { content: "?" }
.fa-mobile-phone::before,.fa-mobile::before { content: "?" }
.fa-circle-o::before { content: "?" }
.fa-quote-left::before { content: "?" }
.fa-quote-right::before { content: "?" }
.fa-spinner::before { content: "?" }
.fa-circle::before { content: "?" }
.fa-mail-reply::before,.fa-reply::before { content: "?" }
.fa-github-alt::before { content: "?" }
.fa-folder-o::before { content: "?" }
.fa-folder-open-o::before { content: "?" }
.fa-smile-o::before { content: "?" }
.fa-frown-o::before { content: "?" }
.fa-meh-o::before { content: "?" }
.fa-gamepad::before { content: "?" }
.fa-keyboard-o::before { content: "?" }
.fa-flag-o::before { content: "?" }
.fa-flag-checkered::before { content: "?" }
.fa-terminal::before { content: "?" }
.fa-code::before { content: "?" }
.fa-mail-reply-all::before,.fa-reply-all::before { content: "?" }
.fa-star-half-empty::before,.fa-star-half-full::before,.fa-star-half-o::before { content: "?" }
.fa-location-arrow::before { content: "?" }
.fa-crop::before { content: "?" }
.fa-code-fork::before { content: "?" }
.fa-unlink::before,.fa-chain-broken::before { content: "?" }
.fa-question::before { content: "?" }
.fa-info::before { content: "?" }
.fa-exclamation::before { content: "?" }
.fa-superscript::before { content: "?" }
.fa-subscript::before { content: "?" }
.fa-eraser::before { content: "?" }
.fa-puzzle-piece::before { content: "?" }
.fa-microphone::before { content: "?" }
.fa-microphone-slash::before { content: "?" }
.fa-shield::before { content: "?" }
.fa-calendar-o::before { content: "?" }
.fa-fire-extinguisher::before { content: "?" }
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pre { font-size: inherit; line-height: inherit }
label { font-weight: normal }
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div.error>h1 { font-size: 500%; line-height: normal }
div.error>p { font-size: 200%; line-height: normal }
div.traceback-wrapper { text-align: left; max-width: 800px; margin: auto }
body { background-color: #fff; position: absolute; left: 0px; right: 0px; top: 0px; bottom: 0px; overflow: visible }
body>#header { display: none; background-color: #fff; position: relative; z-index: 100 }
body>#header #header-container { padding-bottom: 5px; padding-top: 5px }
body>#header .header-bar { width: 100%; height: 1px; background: #e7e7e7; margin-bottom: -1px }
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[dir="rtl"] #ipython_notebook { float: right !important }
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input.ui-button { padding: 0.3em 0.9em }
span#login_widget { float: right }
span#login_widget>.button,#logout { color: #333; background-color: #fff; border-color: #ccc }
span#login_widget>.button:focus,#logout:focus,span#login_widget>.button.focus,#logout.focus { color: #333; background-color: #e6e6e6; border-color: #8c8c8c }
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span#login_widget>.button .badge,#logout .badge { color: #fff; background-color: #333 }
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#header>span { margin-top: 10px }
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ul#tabs { margin-bottom: 4px }
[dir="rtl"] ul#tabs { margin-right: 0px }
ul#tabs a { padding-top: 6px; padding-bottom: 4px }
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ul.breadcrumb i.icon-home { font-size: 16px; margin-right: 4px }
ul.breadcrumb span { color: #5e5e5e }
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div.cell { display: flex; border-width: 1px; border-style: solid; border-color: transparent; width: 100%; padding: 5px; margin: 0px; outline: none; border-left-width: 1px; padding-left: 5px; background: linear-gradient(to right, transparent -40px, transparent 1px, transparent 1px, transparent 100%) }
div.cell.jupyter-soft-selected { border-left-color: #E3F2FD; border-left-width: 1px; padding-left: 5px; border-right-color: #E3F2FD; border-right-width: 1px; background: #E3F2FD }
div.cell.selected { border-color: #ababab; border-left-width: 0px; padding-left: 6px; background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 5px, transparent 5px, transparent 100%) }
div.cell.selected.jupyter-soft-selected { border-left-width: 0; padding-left: 6px; background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 7px, #E3F2FD 7px, #E3F2FD 100%) }
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div.inner_cell { min-width: 0; display: flex }
div.input_area { border: 1px solid #cfcfcf; background: #f7f7f7; line-height: 1.21429em }
div.prompt:empty { padding-top: 0; padding-bottom: 0 }
div.unrecognized_cell { padding: 5px 5px 5px 0px; display: flex }
div.unrecognized_cell .inner_cell { padding: 5px; font-weight: bold; color: red; border: 1px solid #cfcfcf; background: #eaeaea }
div.unrecognized_cell .inner_cell a { color: inherit; text-decoration: none }
div.unrecognized_cell .inner_cell a:hover { color: inherit; text-decoration: none }
div.code_cell { }
div.input { page-break-inside: avoid; display: flex }
div.input_prompt { color: #303F9F; border-top: 1px solid transparent }
div.input_area>div.highlight { margin: 0.4em; border: none; padding: 0px; background-color: transparent }
div.input_area>div.highlight>pre { margin: 0px; border: none; padding: 0px; background-color: transparent }
.CodeMirror { line-height: 1.21429em; font-size: 14px; height: auto; background: none }
.CodeMirror-scroll { }
.CodeMirror-lines { padding: 0.4em }
.CodeMirror-linenumber { padding: 0 8px 0 4px }
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.CodeMirror pre { padding: 0; border: 0 }
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.highlight-variable { color: #000 }
.highlight-variable-2 { color: #1a1a1a }
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.highlight-string { color: #BA2121 }
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.highlight-number { color: #080 }
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.highlight-keyword { color: #008000; font-weight: bold }
.highlight-builtin { color: #008000 }
.highlight-error { color: #f00 }
.highlight-operator { color: #AA22FF; font-weight: bold }
.highlight-meta { color: #AA22FF }
.highlight-def { color: #00f }
.highlight-string-2 { color: #f50 }
.highlight-qualifier { color: #555 }
.highlight-bracket { color: #997 }
.highlight-tag { color: #170 }
.highlight-attribute { color: #00c }
.highlight-header { color: blue }
.highlight-quote { color: #090 }
.highlight-link { color: #00c }
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.cm-s-ipython span.cm-atom { color: #88F }
.cm-s-ipython span.cm-number { color: #080 }
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.cm-s-ipython span.cm-variable { color: #000 }
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.cm-s-ipython span.cm-string { color: #BA2121 }
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.cm-s-ipython span.cm-meta { color: #AA22FF }
.cm-s-ipython span.cm-qualifier { color: #555 }
.cm-s-ipython span.cm-builtin { color: #008000 }
.cm-s-ipython span.cm-bracket { color: #997 }
.cm-s-ipython span.cm-tag { color: #170 }
.cm-s-ipython span.cm-attribute { color: #00c }
.cm-s-ipython span.cm-header { color: blue }
.cm-s-ipython span.cm-quote { color: #090 }
.cm-s-ipython span.cm-link { color: #00c }
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div.output_wrapper { position: relative; display: flex; z-index: 1 }
div.output_scroll { height: 24em; width: 100%; overflow: auto; display: block }
div.output_collapsed { margin: 0px; padding: 0px; display: flex }
div.out_prompt_overlay { height: 100%; padding: 0px 0.4em; position: absolute }
div.out_prompt_overlay:hover { background: rgba(240, 240, 240, 0.5) }
div.output_prompt { color: #D84315 }
div.output_area { padding: 0px; page-break-inside: avoid; display: flex }
div.output_area .MathJax_Display { text-align: left !important }
div.output_area .rendered_html table { margin-left: 0; margin-right: 0 }
div.output_area .rendered_html img { margin-left: 0; margin-right: 0 }
div.output_area img,div.output_area svg { max-width: 100%; height: auto }
div.output_area img.unconfined,div.output_area svg.unconfined { max-width: none }
.output { display: flex }
div.output_area pre { margin: 0; padding: 0; border: 0; vertical-align: baseline; color: black; background-color: transparent }
div.output_subarea { padding: 0.4em; max-width: calc(100% - 14ex) }
div.output_scroll div.output_subarea { }
div.output_text { text-align: left; color: #000; line-height: 1.21429em }
div.output_stderr { background: #fdd }
div.output_latex { text-align: left }
div.output_javascript:empty { padding: 0 }
.js-error { color: darkred }
div.raw_input_container { line-height: 1.21429em; padding-top: 5px }
pre.raw_input_prompt { }
input.raw_input { font-family: monospace; font-size: inherit; color: inherit; width: auto; vertical-align: baseline; padding: 0em 0.25em; margin: 0em 0.25em }
input.raw_input:focus { }
p.p-space { margin-bottom: 10px }
div.output_unrecognized { padding: 5px; font-weight: bold; color: red }
div.output_unrecognized a { color: inherit; text-decoration: none }
div.output_unrecognized a:hover { color: inherit; text-decoration: none }
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.rendered_html em { font-style: italic }
.rendered_html strong { font-weight: bold }
.rendered_html u { text-decoration: underline }
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.rendered_html h6:first-child { margin-top: 1em }
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.rendered_html ol { list-style: decimal; margin: 0em 2em; padding-left: 0px }
.rendered_html ol ol { list-style: upper-alpha; margin: 0em 2em }
.rendered_html ol ol ol { list-style: lower-alpha; margin: 0em 2em }
.rendered_html ol ol ol ol { list-style: lower-roman; margin: 0em 2em }
.rendered_html ol ol ol ol ol { list-style: decimal; margin: 0em 2em }
.rendered_html *+ul { margin-top: 1em }
.rendered_html *+ol { margin-top: 1em }
.rendered_html hr { color: black; background-color: black }
.rendered_html pre { margin: 1em 2em }
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.rendered_html blockquote { margin: 1em 2em }
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.rendered_html td,.rendered_html th { text-align: left; vertical-align: middle; padding: 4px }
.rendered_html th { font-weight: bold }
.rendered_html *+table { margin-top: 1em }
.rendered_html p { text-align: left }
.rendered_html *+p { margin-top: 1em }
.rendered_html img { display: block; margin-left: auto; margin-right: auto }
.rendered_html *+img { margin-top: 1em }
.rendered_html img,.rendered_html svg { max-width: 100%; height: auto }
.rendered_html img.unconfined,.rendered_html svg.unconfined { max-width: none }
div.text_cell { display: flex }
div.text_cell_render { outline: none; width: inherit; border-style: none; padding: 0.5em 0.5em 0.5em 0.4em; color: #000 }
a.anchor-link:link { text-decoration: none; padding: 0px 20px; visibility: hidden }
h1:hover .anchor-link,h2:hover .anchor-link,h3:hover .anchor-link,h4:hover .anchor-link,h5:hover .anchor-link,h6:hover .anchor-link { visibility: visible }
.text_cell.rendered .input_area { display: none }
.text_cell.rendered .rendered_html { }
.text_cell.unrendered .text_cell_render { display: none }
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.cm-header-5 { font-size: 100%; font-style: italic }
.cm-header-6 { font-size: 100%; font-style: italic }
#ipython-main-app { height: 100% }
div#notebook_panel { margin: 0px; padding: 0px; height: 100% }
div#notebook { font-size: 14px; line-height: 20px; width: 100%; padding-top: 20px; margin: 0px; outline: none; min-height: 100% }
div.ui-widget-content { border: 1px solid #ababab; outline: none }
pre.dialog { background-color: #f7f7f7; border: 1px solid #ddd; padding: 0.4em; padding-left: 2em }
p.dialog { padding: 0.2em }
pre,code,kbd,samp { white-space: pre-wrap }
#fonttest { font-family: monospace }
p { margin-bottom: 0 }
.end_space { min-height: 100px }
.notebook_app>#header { }
kbd { border-style: solid; border-width: 1px; margin: 2px; padding-left: 2px; padding-right: 2px; padding-top: 1px; padding-bottom: 1px }
.celltoolbar { border: thin solid #CFCFCF; border-bottom: none; background: #EEE; width: 100%; height: 29px; padding-right: 4px; display: -webkit-flex }
.ctb_hideshow { display: none; vertical-align: bottom }
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.celltoolbar select { color: #555555; background-color: #fff; background-image: none; border: 1px solid #ccc; line-height: 1.5; width: inherit; font-size: inherit; height: 22px; padding: 0px; display: inline-block }
.celltoolbar select:focus { border-color: #66afe9; outline: 0 }
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.celltoolbar select:-ms-input-placeholder { color: #999 }
.celltoolbar select::-webkit-input-placeholder { color: #999 }
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textarea.celltoolbar select { height: auto }
select.celltoolbar select { height: 30px; line-height: 30px }
textarea.celltoolbar select,select[multiple].celltoolbar select { height: auto }
.celltoolbar label { margin-left: 5px; margin-right: 5px }
.completions { position: absolute; z-index: 110; overflow: hidden; border: 1px solid #ababab; line-height: 1 }
.completions select { background: white; outline: none; border: none; padding: 0px; margin: 0px; overflow: auto; font-family: monospace; font-size: 110%; color: #000; width: auto }
.completions select option.context { color: #286090 }
#kernel_logo_widget { float: right }
#kernel_logo_widget .current_kernel_logo { display: none; margin-top: -1px; margin-bottom: -1px; width: 32px; height: 32px }
#menubar { margin-top: 1px }
#menubar .navbar { border-top: 1px; margin-bottom: 0px }
#menubar .navbar-toggle { float: left; padding-top: 7px; padding-bottom: 7px; border: none }
#menubar .navbar-collapse { clear: left }
.nav-wrapper { border-bottom: 1px solid #e7e7e7 }
i.menu-icon { padding-top: 4px }
ul#help_menu li a { overflow: hidden; padding-right: 2.2em }
ul#help_menu li a i { margin-right: -1.2em }
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.dropdown-submenu>a::after.pull-right { margin-left: .3em }
.dropdown-submenu:hover>a::after { color: #262626 }
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.dropdown-submenu.pull-left>.dropdown-menu { left: -100%; margin-left: 10px }
#notification_area { float: right; z-index: 10 }
.indicator_area { float: right; color: #777; margin-left: 5px; margin-right: 5px; z-index: 10; text-align: center; width: auto }
#kernel_indicator { float: right; color: #777; margin-left: 5px; margin-right: 5px; z-index: 10; text-align: center; width: auto; border-left: 1px solid }
#kernel_indicator .kernel_indicator_name { padding-left: 5px; padding-right: 5px }
#modal_indicator { float: right; color: #777; margin-left: 5px; margin-right: 5px; z-index: 10; text-align: center; width: auto }
#readonly-indicator { float: right; color: #777; z-index: 10; text-align: center; width: auto; margin-top: 2px; margin-bottom: 0px; margin-left: 0px; margin-right: 0px; display: none }
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.notification_widget .badge { color: #fff; background-color: #333 }
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.notification_widget.info { color: #fff; background-color: #5bc0de; border-color: #46b8da }
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.notification_widget.danger { color: #fff; background-color: #d9534f; border-color: #d43f3a }
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In [1]:

# from http://pandas.pydata.org/pandas-docs/stable/indexing.html
# pandas 0.22.0

In [2]:

import pandas as pd
import numpy as np

In [3]:

"""
尽量利用pandas提供的专用索引方式，而不是python通用的切片方式。
三种主要的索引方式：indexers
.loc label based 基于标签， 可以是标签名，可以是布尔值，可以是一元函数
.iloc integer psition based 基于整数位置(from 0 to length-1 of the axis)，和python切片类似
[]

"""

"""
Object Type 		Selection 			Return Value Type
------------------------------------------------------------
Series 				series[label] 		scalar value
DataFrame 			frame[colname] 		Series corresponding to colname
Panel 				panel[itemname] 	DataFrame corresponding to the itemname
"""

Out[3]:

‘\n尽量利用pandas提供的专用索引方式，而不是python通用的切片方式。\n三种主要的索引方式：indexers\n.loc label based 基于标签， 可以是标签名，可以是布尔值，可以是一元函数\n.iloc integer psition based 基于整数位置(from 0 to length-1 of the axis)，和python切片类似\n[]\n\n‘

Out[3]:

‘\nObject Type \t\tIndexers\nSeries \t\t\t\ts.loc[indexer]\nDataFrame \t\t\tdf.loc[row_indexer,column_indexer]\nPanel \t\t\t\tp.loc[item_indexer,major_indexer,minor_indexer]\n‘

In [5]:

# Here we construct a simple time series data set to use for illustrating the indexing functionality
# 构造时间序列，举例说明索引的功能

dates = pd.date_range(‘1/1/2000‘, periods=8)
dates
df = pd.DataFrame(np.random.randn(8, 4), index=dates, columns=[‘A‘, ‘B‘, ‘C‘, ‘D‘])
df

Out[5]:

DatetimeIndex([‘2000-01-01‘, ‘2000-01-02‘, ‘2000-01-03‘, ‘2000-01-04‘,
               ‘2000-01-05‘, ‘2000-01-06‘, ‘2000-01-07‘, ‘2000-01-08‘],
              dtype=‘datetime64[ns]‘, freq=‘D‘)

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In [8]:

panel = pd.Panel({‘one‘ : df, ‘two‘ : df - df.mean()})  # 多维表格
panel
panel[‘one‘]
panel[‘two‘]

Out[8]:

<class ‘pandas.core.panel.Panel‘>
Dimensions: 2 (items) x 8 (major_axis) x 4 (minor_axis)
Items axis: one to two
Major_axis axis: 2000-01-01 00:00:00 to 2000-01-08 00:00:00
Minor_axis axis: A to D

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In [9]:

# Thus, as per above, we have the most basic indexing using []:
# 最基本的索引方法，使用[]

s = df[‘A‘]
s
dates[5]  # 注意切片从0计数
s[dates[5]]

Out[9]:

2000-01-01    0.136628
2000-01-02    0.113819
2000-01-03   -0.603598
2000-01-04   -0.486200
2000-01-05    0.835318
2000-01-06   -2.376205
2000-01-07    0.193371
2000-01-08    0.476533
Freq: D, Name: A, dtype: float64

Out[9]:

Timestamp(‘2000-01-06 00:00:00‘, freq=‘D‘)

Out[9]:

-2.376204948581219

In [12]:

# 在[]中传入列名的列表，如[ ‘A‘, "B" ]
columns_l = [‘A‘, ‘B‘]
df[columns_l]
df[[ ‘A‘, "B" ]]  # 相当于上面，注意两重[]
df

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In [17]:

df[[‘A‘, ‘B‘]] = df[[‘B‘, ‘A‘]]  # 交换两列的值
df
df.loc[:,[‘B‘, ‘A‘]]

# 下式不能交换两列的值
# This will not modify df because the column alignment is before value assignment. ? 不理解？
# 列赋值在值赋值之前？
df.loc[:,[‘B‘, ‘A‘]] = df[[‘A‘, ‘B‘]]
df

# df.loc[:,[‘B‘, ‘A‘]] = df[:, [‘A‘, ‘B‘]]   # 错误？
# df

# 正确的方式：
df.loc[:,[‘B‘, ‘A‘]] = df[[‘A‘, ‘B‘]].values  # 取列的值
df

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Out[17]:

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In [18]:

# Attribute Access?
# 属性访问，属性存取
# You may access an index on a Series, column on a DataFrame,
# and an item on a Panel directly as an attribute:

sa = pd.Series([1,2,3],index=list(‘abc‘))
sa

dfa = df.copy()
dfa

Out[18]:

a    1
b    2
c    3
dtype: int64

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In [20]:

# 对item column等赋值
# 就像属性一样的存取，但需要注意：
# 1. 名称应符合python命名规则，由字母、数字和下划线组成
# 2. 不能和已有的方法名称重名，例如 min
# 3. 不能与pandas内部“关键字”重名，例如 index axis items labels
# 以上情况，可以使用 [ "" ] 引用

sa.a = 5
sa

dfa.index
dfa.A = list(range(len(dfa.index)))
dfa

Out[20]:

a    5
b    2
c    3
dtype: int64

Out[20]:

DatetimeIndex([‘2000-01-01‘, ‘2000-01-02‘, ‘2000-01-03‘, ‘2000-01-04‘,
               ‘2000-01-05‘, ‘2000-01-06‘, ‘2000-01-07‘, ‘2000-01-08‘],
              dtype=‘datetime64[ns]‘, freq=‘D‘)

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In [21]:

x = pd.DataFrame({‘x‘: [1, 2, 3], ‘y‘: [3, 4, 5]})  # 字典key值为列名
x

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In [24]:

dict(x=9, y=99)
x.iloc[1]
x.iloc[1] = dict(x=9, y=99)
x

Out[24]:

{‘x‘: 9, ‘y‘: 99}

Out[24]:

x    2
y    4
Name: 1, dtype: int64

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In [29]:

df = pd.DataFrame({‘one‘: [1., 2., 3.]})
df
df.two = [4, 5, 6]  # 错误，不能增加一列，利用属性的方式不能对没有的列赋值
df.two  # 但是增加了一项属性，而且可以取得这项属性
df
df[‘two‘] = [4, 5, 6]  # 可以增加一列
df

Out[29]:

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d:\python\36-64\lib\site-packages\ipykernel_launcher.py:3: UserWarning: Pandas doesn‘t allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access
  This is separate from the ipykernel package so we can avoid doing imports until

Out[29]:

[4, 5, 6]

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In [31]:

# Slicing ranges
# 切片范围
# iloc 方法是最稳健和兼容的
# 下面介绍 方括号 [] 操作符 作为切片

# 对series操作
# 取值
s
s[:5]
s[::2]
s[::-1]

Out[31]:

2000-01-01    0.324097
2000-01-02   -0.718630
2000-01-03   -0.143643
2000-01-04   -0.136663
2000-01-05    1.036607
2000-01-06    0.362577
2000-01-07    1.330468
2000-01-08   -0.476653
Freq: D, Name: A, dtype: float64

Out[31]:

2000-01-01    0.324097
2000-01-02   -0.718630
2000-01-03   -0.143643
2000-01-04   -0.136663
2000-01-05    1.036607
Freq: D, Name: A, dtype: float64

Out[31]:

2000-01-01    0.324097
2000-01-03   -0.143643
2000-01-05    1.036607
2000-01-07    1.330468
Freq: 2D, Name: A, dtype: float64

Out[31]:

2000-01-08   -0.476653
2000-01-07    1.330468
2000-01-06    0.362577
2000-01-05    1.036607
2000-01-04   -0.136663
2000-01-03   -0.143643
2000-01-02   -0.718630
2000-01-01    0.324097
Freq: -1D, Name: A, dtype: float64

In [33]:

# 赋值
s2 = s.copy()
s2
s2[:5] = 0
s2

Out[33]:

2000-01-01    0.324097
2000-01-02   -0.718630
2000-01-03   -0.143643
2000-01-04   -0.136663
2000-01-05    1.036607
2000-01-06    0.362577
2000-01-07    1.330468
2000-01-08   -0.476653
Freq: D, Name: A, dtype: float64

Out[33]:

2000-01-01    0.000000
2000-01-02    0.000000
2000-01-03    0.000000
2000-01-04    0.000000
2000-01-05    0.000000
2000-01-06    0.362577
2000-01-07    1.330468
2000-01-08   -0.476653
Freq: D, Name: A, dtype: float64

In [35]:

# 对DataFrame操作
# [] 操作 选择的是行
df
df[:3]
df[::-1]

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In [49]:

# Selection By Label
# 通过标签选择

# 这种方式可能依靠上下文关系，有时候会调用链式赋值，这应该避免。参考：
# Returning a view versus a copy 返回视图 对比 拷贝

# When setting values in a pandas object,
# care must be taken to avoid what is called chained indexing.
# Here is an example.

[list(‘abcd‘),list(‘efgh‘),list(‘ijkl‘),list(‘mnop‘)]
[[‘one‘,‘two‘],[‘first‘,‘second‘]]

dfmi = pd.DataFrame([list(‘abcd‘),list(‘efgh‘),list(‘ijkl‘),list(‘mnop‘)],  # 定义四列数值
        columns=pd.MultiIndex.from_product(
         [[‘one‘,‘two‘],[‘first‘,‘second‘]])) # 定义多重索引，第一个list是第一层，以下类推

dfmi

Out[49]:

[[‘a‘, ‘b‘, ‘c‘, ‘d‘],
 [‘e‘, ‘f‘, ‘g‘, ‘h‘],
 [‘i‘, ‘j‘, ‘k‘, ‘l‘],
 [‘m‘, ‘n‘, ‘o‘, ‘p‘]]

Out[49]:

[[‘one‘, ‘two‘], [‘first‘, ‘second‘]]

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In [50]:

#  Compare these two access methods:
dfmi[‘one‘][‘second‘]  # chained
dfmi.loc[:,(‘one‘,‘second‘)]

Out[50]:

0    b
1    f
2    j
3    n
Name: second, dtype: object

Out[50]:

0    b
1    f
2    j
3    n
Name: (one, second), dtype: object

In [40]:

# 两种方式分析

# 第一种方式：链式 使用两个 []
dfmi[‘one‘]  # 第一个[] 先生成了一个DataFrame
dfmi[‘one‘][‘second‘]  # pandas 把两个[] 作为分开的事件，他们执行分开的两步调用 __getitem__

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In [53]:

# 第二种方式：loc
# 通过嵌套的元组切片
df_s = (slice(None), (‘one‘, ‘second‘))
dfmi.loc[df_s]  # 只调用了一次 __getitem__

Out[53]:

0    b
1    f
2    j
3    n
Name: (one, second), dtype: object

In [62]:

# Selection By Label
# 通过标签选择

# loc要注意索引的数据类型，必须与索引的数据类型一致才可以，
# 例如 datetimeIndex 中，使用loc[2:3] ，即整数型的slice 将会出现TypeError

dfl = pd.DataFrame(np.random.randn(5,4), columns=list(‘ABCD‘),
                   index=pd.date_range(‘20130101‘,periods=5))

dfl
# dfl.loc[2:3]  # 错误的loc
dfl.loc[‘20130102‘:‘20130104‘]  # 使用可转换为datetime的字符串
dfl.loc[‘20130202‘:‘20130204‘]  # 不报错，返回为空DataFrame
# dfl.loc[‘20130202‘]  # 报错，错误信息是index无此值
dfl.loc[‘20130104‘:‘20130114‘]  # 只返回存在的数据

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In [64]:

# loc可以使用整数，但此时的整数不代表位置，而是label
# loc是基本的取值方法
# 给loc的输入，即在[]中的值，可以是：
# 1. 单独的label  e.g. 5 or ‘a
# 2. labels的list   [‘a‘, ‘b‘, ‘c‘]
# 3. slice对象  ‘a‘:‘f‘  !! 注意：与python的切片不同，pandas的切片包括开始和结尾，而python不包括结尾
# 4. 布尔值
# 5. 调用函数  [lambda df: df.A > 0, :]

# Series
s1 = pd.Series(np.random.randn(6),index=list(‘abcdef‘))
s1
s1.loc[‘c‘:]
s1.loc[‘b‘]
s1.loc[‘c‘:] = 0
s1

Out[64]:

a    0.796911
b   -1.341250
c    0.008152
d   -0.745881
e    0.674385
f    1.108411
dtype: float64

Out[64]:

c    0.008152
d   -0.745881
e    0.674385
f    1.108411
dtype: float64

Out[64]:

-1.3412499335785426

Out[64]:

a    0.796911
b   -1.341250
c    0.000000
d    0.000000
e    0.000000
f    0.000000
dtype: float64

In [65]:

# DataFrame
df1 = pd.DataFrame(np.random.randn(6,4),  # 6X4 阵列
                   index=list(‘abcdef‘),  # 索引
                   columns=list(‘ABCD‘))  # 行号
df1

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In [72]:

df1.loc[[‘a‘, ‘b‘, ‘d‘], :]  # 先是行label选择，再是列label选择
df1.loc[‘d‘:, ‘A‘:‘C‘]

# 取得 a cross section 截面，用单个的label，返回Series
# 以下三式等同
df1.loc[‘a‘]
df1.loc[‘a‘,:]
df1.xs(‘a‘)
type(df1.loc[‘a‘])

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Out[72]:

A   -1.912141
B   -0.835589
C   -0.188341
D   -1.024797
Name: a, dtype: float64

Out[72]:

A   -1.912141
B   -0.835589
C   -0.188341
D   -1.024797
Name: a, dtype: float64

Out[72]:

A   -1.912141
B   -0.835589
C   -0.188341
D   -1.024797
Name: a, dtype: float64

Out[72]:

pandas.core.series.Series

In [73]:

# 通过布尔值数组取值
df1.loc[‘a‘] > 0
df1.loc[:, df1.loc[‘a‘] > 0]

Out[73]:

A    False
B    False
C    False
D    False
Name: a, dtype: bool

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In [74]:

# 获取一个值
# this is also equivalent to ``df1.at[‘a‘,‘A‘]``
df1.loc[‘a‘, ‘A‘]
df1.at[‘a‘,‘A‘]

Out[74]:

-1.9121410098540752

Out[74]:

-1.9121410098540752

In [75]:

# Slicing with labels?
# 用labels切片
s = pd.Series(list(‘abcde‘), index=[0,3,2,5,4])
s
s.loc[3:5]  # 包含 5， 注意不是 3 4 5 ，而是从 标签3 到 标签5

Out[75]:

0    a
3    b
2    c
5    d
4    e
dtype: object

Out[75]:

3    b
2    c
5    d
dtype: object

In [80]:

# s.loc[3:6]  # 2个错误，ValueError: index must be monotonic increasing or decreasing  KeyError: 6
# 如果排序的话，可以超出范围
s.sort_index()  # 不改变原值
s
s.sort_index().loc[1:6]  # 可以超出范围
s.sort_index().loc[6:8]  # 即使一个都没有
# s.sort_index().loc[8]  # 但不能是单值，必须是切片

Out[80]:

0    a
2    c
3    b
4    e
5    d
dtype: object

Out[80]:

0    a
3    b
2    c
5    d
4    e
dtype: object

Out[80]:

2    c
3    b
4    e
5    d
dtype: object

Out[80]:

Series([], dtype: object)

In [82]:

# Selection By Position
# 通过位置选择，仅通过基于索引的整数，与python和numpy类似，从0开始，且不包括最后一个
# iloc的输入：
# 1. 整数
# 2. 整数的list
# 3. 整数的切片
# 4. 布尔值数组
# 5. 调用函数

# Series
s1 = pd.Series(np.random.randn(5), index=list(range(0,10,2)))
s1
s1.iloc[:3]
s1.iloc[3]
s1.iloc[:3] = 0
s1

Out[82]:

0   -0.312716
2    1.425936
4    1.716575
6    2.099666
8    0.262365
dtype: float64

Out[82]:

0   -0.312716
2    1.425936
4    1.716575
dtype: float64

Out[82]:

2.099665679869975

Out[82]:

0    0.000000
2    0.000000
4    0.000000
6    2.099666
8    0.262365
dtype: float64

In [83]:

# DataFrame
df1 = pd.DataFrame(np.random.randn(6,4),
                  index=list(range(0,12,2)),
                  columns=list(range(0,8,2)))
df1

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In [87]:

df1.iloc[:3]
df1.iloc[1:5, 2:4]
df1.iloc[[1, 3, 5], [1, 3]]
df1.iloc[1:3, :]
df1.iloc[:, 1:3]

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In [89]:

# this is also equivalent to ``df1.iat[1,1]``
# 取单个的值
df1.iloc[1, 1]
df1.iat[1, 1]

Out[89]:

0.2759774784621013

Out[89]:

0.2759774784621013

In [92]:

# For getting a cross section using an integer position (equiv to df.xs(1))
# 取截面，得到Series
df1.iloc[1]
df1.iloc[:,1]

Out[92]:

0    0.173188
2    0.275977
4   -0.044987
6   -1.077772
Name: 2, dtype: float64

Out[92]:

0    -0.512450
2     0.275977
4     1.604020
6    -0.102090
8    -1.232141
10    1.009840
Name: 2, dtype: float64

In [93]:

# Out of range slice indexes are handled gracefully just as in Python/Numpy.
# 超过索引的切片处理，与python和numpy一样
# 注意：不能是单独索引，或列表中，有超过界限的值，只可以是slice，即带冒号的切片才不会提示错误

x = list(‘abcdef‘)
x[4:10]
x[8:10]
s = pd.Series(x)
s.iloc[4:10]
s.iloc[8:10]  # 超过界限bound返回空

Out[93]:

[‘e‘, ‘f‘]

Out[93]:

[]

Out[93]:

4    e
5    f
dtype: object

Out[93]:

Series([], dtype: object)

In [94]:

dfl = pd.DataFrame(np.random.randn(5,2), columns=list(‘AB‘))
dfl
dfl.iloc[:, 2:3]
dfl.iloc[:, 1:3]
dfl.iloc[4:6]

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In [99]:

# Selection By Callable
# 通过调用函数进行选择

df1 = pd.DataFrame(np.random.randn(6,4),
                  index=list("abcdef"),
                  columns=list("ABCD"))
df1
df1.A

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Out[99]:

a   -1.947578
b    0.565255
c   -1.275992
d    0.433325
e    0.341412
f    1.518936
Name: A, dtype: float64

In [100]:

df1.loc[lambda df: df.A > 0, :]
df1.loc[:, lambda df: [‘A‘, ‘B‘]]
df1.iloc[:, lambda df: [0, 1]]
df1[lambda df: df.columns[0]]

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Out[100]:

a   -1.947578
b    0.565255
c   -1.275992
d    0.433325
e    0.341412
f    1.518936
Name: A, dtype: float64

In [101]:

df1.A
df1.A.loc[lambda s: s > 0]
df1.A.loc[df1.A > 0]

Out[101]:

a   -1.947578
b    0.565255
c   -1.275992
d    0.433325
e    0.341412
f    1.518936
Name: A, dtype: float64

Out[101]:

b    0.565255
d    0.433325
e    0.341412
f    1.518936
Name: A, dtype: float64

Out[101]:

b    0.565255
d    0.433325
e    0.341412
f    1.518936
Name: A, dtype: float64

In [ ]:

# 使用这些方法或索引，可以使用链式的选择方法，而不用中间的临时变量。链式方法，不是链式[]
bb = pd.read_csv(‘data/baseball.csv‘, index_col=‘id‘)
bb.groupby([‘year‘, ‘team‘]).sum().loc[lambda df: df.r > 100]

In [102]:

# IX Indexer is Deprecated
# 不推荐使用ix
# in favor of the more strict .iloc and .loc indexers.
# 使用.iloc和.loc代替.ix

dfd = pd.DataFrame({‘A‘: [1, 2, 3],‘B‘: [4, 5, 6]},index=list(‘abc‘))
dfd

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In [103]:

dfd.ix[[0, 2], ‘A‘]

d:\python\36-64\lib\site-packages\ipykernel_launcher.py:1: DeprecationWarning:
.ix is deprecated. Please use
.loc for label based indexing or
.iloc for positional indexing

See the documentation here:
http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated
  """Entry point for launching an IPython kernel.

Out[103]:

a    1
c    3
Name: A, dtype: int64

In [105]:

dfd.index[[0, 2]]  # 取得索引的名称
dfd.loc[dfd.index[[0, 2]], ‘A‘]
dfd.columns.get_loc(‘A‘)  # 取得列的索引值
dfd.iloc[[0, 2], dfd.columns.get_loc(‘A‘)]

Out[105]:

Index([‘a‘, ‘c‘], dtype=‘object‘)

Out[105]:

a    1
c    3
Name: A, dtype: int64

Out[105]:

0

Out[105]:

a    1
c    3
Name: A, dtype: int64

In [106]:

# Indexing with list with missing labels is Deprecated
# 不推荐用有缺失标签的list进行索引
# using .loc or [] with a list with one or more missing labels, is deprecated, in favor of .reindex.
# 推荐使用.reindex

s = pd.Series([1, 2, 3])
s

Out[106]:

0    1
1    2
2    3
dtype: int64

In [107]:

s.loc[[1, 2]]  # list中的keys都存在，则没有变化

Out[107]:

1    2
2    3
dtype: int64

In [108]:

s.loc[[1, 2, 3]]  # 当有缺失时，赋值为NaN

d:\python\36-64\lib\site-packages\ipykernel_launcher.py:1: FutureWarning:
Passing list-likes to .loc or [] with any missing label will raise
KeyError in the future, you can use .reindex() as an alternative.

See the documentation here:
http://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike
  """Entry point for launching an IPython kernel.

Out[108]:

1    2.0
2    3.0
3    NaN
dtype: float64

In [109]:

# Reindexing

s.reindex([1, 2, 3])

Out[109]:

1    2.0
2    3.0
3    NaN
dtype: float64

In [110]:

# 如果仅选择有效的keys
labels = [1, 2, 3]
s.index.intersection(labels)  # index和labes的交集
s.loc[s.index.intersection(labels)]

Out[110]:

Int64Index([1, 2], dtype=‘int64‘)

Out[110]:

1    2
2    3
dtype: int64

In [112]:

# reindex 索引中不能有重复的项
s = pd.Series(np.arange(4), index=[‘a‘, ‘a‘, ‘b‘, ‘c‘])
s
labels = [‘c‘, ‘d‘]
# s.reindex(labels)  # 不能reindex

Out[112]:

a    0
a    1
b    2
c    3
dtype: int32

In [113]:

# 可以先把交集切出来，再进行reindex
# 但是交集不能有重复的index
s.index.intersection(labels)
s.loc[s.index.intersection(labels)]
s.loc[s.index.intersection(labels)].reindex(labels)

Out[113]:

Index([‘c‘], dtype=‘object‘)

Out[113]:

c    3
dtype: int32

Out[113]:

c    3.0
d    NaN
dtype: float64

In [114]:

# Selecting Random Samples
# 随机取样选择
# 默认行取样

s = pd.Series([0,1,2,3,4,5])
s

Out[114]:

0    0
1    1
2    2
3    3
4    4
5    5
dtype: int64

In [129]:

s.sample()  # 默认取1行
s.sample(n=3)  # 取3行
s.sample(frac=0.5)  # 小数，行数百分数
s.sample(frac=0.8)  # 小数
s

Out[129]:

1    1
dtype: int64

Out[129]:

3    3
4    4
5    5
dtype: int64

Out[129]:

2    2
3    3
4    4
dtype: int64

Out[129]:

2    2
1    1
3    3
0    0
5    5
dtype: int64

Out[129]:

0    0
1    1
2    2
3    3
4    4
5    5
dtype: int64

In [132]:

s.sample(n=6, replace=False)  # 默认
s.sample(n=6, replace=True)  # replace，不改变本身
s

Out[132]:

5    5
4    4
1    1
0    0
2    2
3    3
dtype: int64

Out[132]:

0    0
4    4
0    0
2    2
0    0
0    0
dtype: int64

Out[132]:

0    0
1    1
2    2
3    3
4    4
5    5
dtype: int64

In [166]:

# 默认每行都有同样的概率被抽样到，也可以指定每行的概率比重
example_weights = [0, 0, 0.2, 0.2, 0.2, 0.4]
s.sample(n=3, weights=example_weights)

example_weights2 = [0.5, 0, 0, 0, 0, 0]  # 权重将会自动的归一化
s.sample(n=1, weights=example_weights2)

Out[166]:

2    2
3    3
5    5
dtype: int64

Out[166]:

0    0
dtype: int64

In [175]:

# 可以指定DataFrame的某列作为权重
df2 = pd.DataFrame({‘col1‘:[9,8,7,6], ‘weight_column‘:[0.5, 0.4, 0.1, 0]})
df2.sample(n = 3, weights = ‘weight_column‘)

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In [196]:

# 对列进行抽样
df3 = pd.DataFrame({‘col1‘:[1,2,3], ‘col2‘:[2,3,4], ‘col3‘:[3,4,5]})
df3
df3.sample(n=2, axis=1)  # 指定axis=1，对列抽样，抽取的是列的组合
df3.sample(n=2, axis=0)

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In [220]:

# 可以指定random seed 或者 numpy 的 randomState 对象，作为sample 随机数生成器的种子
# 一旦seed确定，随机数不变
df3.sample(n=2, random_state=2)
df3.sample(n=2, random_state=2)
df3.sample(n=2, random_state=200)
df3.sample(n=2, random_state=200)

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In [222]:

# Setting With Enlargement
# loc或[] 操作 可以通过赋值不存在的键扩大Series或Dataframe

# Series
se = pd.Series([1,2,3])
se
se[5] = 5  # append
se

Out[222]:

0    1
1    2
2    3
dtype: int64

Out[222]:

0    1
1    2
2    3
5    5
dtype: int64

In [223]:

# DataFrame

dfi = pd.DataFrame(np.arange(6).reshape(3,2),columns=[‘A‘,‘B‘])
dfi

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In [224]:

dfi.loc[:,‘C‘] = dfi.loc[:,‘A‘]  # enlarge 增加列
dfi

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In [225]:

dfi.loc[3] = 5  # append 增加行
dfi

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In [231]:

# Fast scalar value getting and setting
# 快速取得或设置标量的值
# [] 可以进行很多操作，所以它为了知道你要进行那种操作，会有一点计算开销
# 最快的标量访问方式是使用 at 和 iat 方法，他们可以在所有的数据结构上使用
# at 类似于 loc 基于 label
# iat 类似于 iloc 基于 整数index
s = pd.Series([0,1,2,3,4,5])
s
df = pd.DataFrame(np.random.randn(8, 4), index=dates, columns=[‘A‘, ‘B‘, ‘C‘, ‘D‘])
df

Out[231]:

0    0
1    1
2    2
3    3
4    4
5    5
dtype: int64

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In [233]:

# get value
s.iat[5]
df.at[dates[5], ‘A‘]
df.iat[3, 0]

Out[233]:

5

Out[233]:

0.40643702489386246

Out[233]:

-0.8469710793801154

In [234]:

# set value
df.at[dates[5], ‘E‘] = 7  # 没有列就增加一列，没有值的默认赋值为nan
df

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In [235]:

df.iat[3, 0] = 7
df

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In [236]:

df.at[dates[-1]+1, 0] = 7  # 行和列都扩展了
df

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# Boolean indexing
# 使用布尔向量过滤数据
# 操作符包括：| for or, & for and, and ~ for not ，必须用括号进行分组

In [237]:

s = pd.Series(range(-3, 4))  # 不用把range先list，直接可以series
s

Out[237]:

0   -3
1   -2
2   -1
3    0
4    1
5    2
6    3
dtype: int64

In [238]:

s[s >= 0]  # 直接用series，不用取其值
s[~(s < 0)]
s[(s < -1) | (s > 0.5)]

Out[238]:

3    0
4    1
5    2
6    3
dtype: int64

Out[238]:

3    0
4    1
5    2
6    3
dtype: int64

Out[238]:

0   -3
1   -2
4    1
5    2
6    3
dtype: int64

In [239]:

df[df[‘A‘] > 0]

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In [240]:

# List comprehensions and map method of Series can also be used to produce more complex criteria:
# 列表生成式和map方法 也可以用来生成 更复杂的条件判断

df2 = pd.DataFrame({‘a‘ : [‘one‘, ‘one‘, ‘two‘, ‘three‘, ‘two‘, ‘one‘, ‘six‘],
                     ‘b‘ : [‘x‘, ‘y‘, ‘y‘, ‘x‘, ‘y‘, ‘x‘, ‘x‘],
                     ‘c‘ : np.random.randn(7)})
df2

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In [241]:

# 判别式
criterion = df2[‘a‘].map(lambda x: x.startswith(‘t‘))  # 选择 two 和 three
criterion

Out[241]:

0    False
1    False
2     True
3     True
4     True
5    False
6    False
Name: a, dtype: bool

In [242]:

df2[criterion]  # 根据 a 列的判别式 选择数据表的一部分，包含其他列

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In [243]:

# 等价的方式，但是速度慢一些
df2[[x.startswith(‘t‘) for x in df2[‘a‘]]]  # 不适用map，而是用列表生成式

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In [244]:

# 复合判断
df2[criterion & (df2[‘b‘] == ‘x‘)]  # a 列 和 b 列 均符合某类要求

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In [245]:

# 布尔向量选择 可以与索引选择一并使用
df2.loc[criterion & (df2[‘b‘] == ‘x‘),‘b‘:‘c‘]  # 只选择 b 和 c 两列，不选择c列

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# Indexing with isin
# 用isin索引

In [246]:

# series
# 对列数据进行判断
s = pd.Series(np.arange(5), index=np.arange(5)[::-1], dtype=‘int64‘)
s

Out[246]:

4    0
3    1
2    2
1    3
0    4
dtype: int64

In [248]:

s.isin([2, 4, 6])  # 列数据中是否存在列表中的值，返回布尔值
s[s.isin([2, 4, 6])]  # 可以利用返回的布尔值进行选择

Out[248]:

4    False
3    False
2     True
1    False
0     True
dtype: bool

Out[248]:

2    2
0    4
dtype: int64

In [249]:

# 也可以对index obj 进行筛选
s[s.index.isin([2, 4, 6])]
s.reindex([2, 4, 6])  # reindex不同，列表中没有的值返回了nan，且原来的int64返回了float64数据类型

Out[249]:

4    0
2    2
dtype: int64

Out[249]:

2    2.0
4    0.0
6    NaN
dtype: float64

In [250]:

# 对应多重索引，可以单独选择索引级别
s_mi = pd.Series(np.arange(6),index=pd.MultiIndex.from_product([[0, 1], [‘a‘, ‘b‘, ‘c‘]]))
s_mi

Out[250]:

0  a    0
   b    1
   c    2
1  a    3
   b    4
   c    5
dtype: int32

In [252]:

s_mi.iloc[s_mi.index.isin([(1, ‘a‘), (2, ‘b‘), (0, ‘c‘)])]
s_mi.iloc[s_mi.index.isin([‘a‘, ‘c‘, ‘e‘], level=1)]  # 指定索引级别，在第二级索引中选择

Out[252]:

0  c    2
1  a    3
dtype: int32

Out[252]:

0  a    0
   c    2
1  a    3
   c    5
dtype: int32

In [253]:

# DataFrame
df = pd.DataFrame({‘vals‘: [1, 2, 3, 4], ‘ids‘: [‘a‘, ‘b‘, ‘f‘, ‘n‘],‘ids2‘: [‘a‘, ‘n‘, ‘c‘, ‘n‘]})
df

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In [254]:

values = [‘a‘, ‘b‘, 1, 3]
df.isin(values)  # 匹配所有的值

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In [262]:

values = {‘ids‘: [‘a‘, ‘b‘], ‘ids2‘: [‘a‘, ‘c‘], ‘vals‘: [1, 3]}
row_mask = df.isin(values)  # 对不用的列，分别匹配某些值
row_mask
# ?row_mask.all  # Return whether all elements are True over requested axis
row_mask = row_mask.all(1)
row_mask
df[row_mask]  # 选择全是True的行

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0     True
1    False
2    False
3    False
dtype: bool

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In [264]:

# The where() Method and Masking
# To guarantee that selection output has the same shape as the original data
# 保证选集输出与原数据有同样的shape形态

# series
s
s[s > 0]  # 只返回满足的项
s.where(s > 0)  # 全部返回，不满足的项，赋值nan

Out[264]:

4    0
3    1
2    2
1    3
0    4
dtype: int64

Out[264]:

3    1
2    2
1    3
0    4
dtype: int64

Out[264]:

4    NaN
3    1.0
2    2.0
1    3.0
0    4.0
dtype: float64

In [267]:

# DataFrame 使用布尔值选择时，返回值保留原数据结构
df = pd.DataFrame(np.random.randn(8, 4), index=dates, columns=[‘A‘, ‘B‘, ‘C‘, ‘D‘])
df

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In [268]:

df[df < 0]
df.where(df < 0)  # 等价于上式
df.where(df < 0, -df)  # where 可以传入另一个参数，用于替换条件为 False 的项，返回copy数据拷贝，不修改原值
df

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In [270]:

# You may wish to set values based on some boolean criteria. This can be done intuitively like so:
# 设置基于布尔值的项值

s2 = s.copy()
s2
s2[s2 < 3] = 0
s2
df2 = df.copy()
df2
df2[df2 < 0] = 0
df2

Out[270]:

4    0
3    1
2    2
1    3
0    4
dtype: int64

Out[270]:

4    0
3    0
2    0
1    3
0    4
dtype: int64

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In [271]:

# where 默认返回修改后的数据拷贝，原值不变；可以设置inplace参数，直接修改原值，而不是创建拷贝

df_orig = df.copy()
df_orig.where(df > 0, -df, inplace=True)
df_orig

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# 注意 ：pandas 和 numpy 的where方法不一样
# 一般的，df1.where(m, df2)  相当于 np.where(m, df1, df2)

df.where(df < 0, -df) == np.where(df < 0, df, -df)

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In [276]:

# alignment 定位，对齐
# where 可以选择局部（部分区域）的布尔条件
# This is analogous to partial setting via .loc (but on the contents rather than the axis labels)

df2 = df.copy()
df2
df2[1:4]   # 行选择
df2.where(df2[1:4] > 0, 3)  # 对不符合项的值进行赋值！
df2[ df2[1:4] > 0 ] = 3  # 只定位部分区域，对符合项的值进行赋值
df2

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In [279]:

# Where can also accept axis and level parameters to align the input when performing the where.
# where 可以接受 轴参数axis 和 级别参数level
df2 = df.copy()
df2
df2.where(df2>0,df2[‘A‘],axis=‘index‘)  # 小于等于0的值，赋值为A列的值
df2
df2.apply(lambda x, y: x.where(x>0,y), y=df[‘A‘])  # 相当于上式，但此式较慢，同样不改变原值，而是生成一个拷贝copy
df2

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In [280]:

# where 可以接受一个函数调用，此函数只能有一个参数，且返回有效的布尔条件
df3 = pd.DataFrame({‘A‘: [1, 2, 3],‘B‘: [4, 5, 6],‘C‘: [7, 8, 9]})
df3
df3.where(lambda x: x > 4, lambda x: x + 10)  # x<=4 的值 赋值为  x+10

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In [282]:

# mask 遮罩 mask is the inverse boolean operation of where. 反向的布尔值操作
s
s.mask(s >= 0)  # 选择<0 的值， 不符合项 置为nan
df
df.mask(df >= 0)

Out[282]:

4    0
3    1
2    2
1    3
0    4
dtype: int64

Out[282]:

4   NaN
3   NaN
2   NaN
1   NaN
0   NaN
dtype: float64

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In [288]:

# The query() Method (Experimental) 对 DataFrame对象 使用表达式进行选择

# 例如 ：选择b列中 在a列和c列两值中间的 行,a<b<c
n = 10
df = pd.DataFrame(np.random.rand(n, 3), columns=list(‘abc‘))
df

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In [289]:

# pure python
df[(df.a < df.b) & (df.b < df.c)]

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In [290]:

# query，传入的是str表达式
df.query(‘(a < b) & (b < c)‘)  # 比纯py慢？！

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In [302]:

# 对于命名的index索引是低效的，比利用列名称
# 而且如果索引的名称和列名同名，列名优先
df = pd.DataFrame(np.random.randint(n / 2, size=(n, 2)), columns=list(‘bc‘))
# df
df.index.name = "a"
df

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In [303]:

df.query(‘a <= b and b <= c‘)

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In [305]:

# 可以不使用索引的名称，而是直接用index，这样同时可以避免与列名重名
df.query(‘index <= b <= c‘)

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In [307]:

# MultiIndex query() Syntax
# 对于多重索引

n = 10
colors = np.random.choice([‘red‘, ‘green‘], size=n)
colors
foods = np.random.choice([‘eggs‘, ‘ham‘], size=n)
foods

Out[307]:

array([‘green‘, ‘green‘, ‘green‘, ‘green‘, ‘green‘, ‘green‘, ‘green‘,
       ‘red‘, ‘green‘, ‘green‘], dtype=‘<U5‘)

Out[307]:

array([‘ham‘, ‘eggs‘, ‘eggs‘, ‘eggs‘, ‘eggs‘, ‘ham‘, ‘eggs‘, ‘eggs‘,
       ‘ham‘, ‘ham‘], dtype=‘<U4‘)

In [308]:

index = pd.MultiIndex.from_arrays([colors, foods], names=[‘color‘, ‘food‘])
index
df = pd.DataFrame(np.random.randn(n, 2), index=index)
df

Out[308]:

MultiIndex(levels=[[‘green‘, ‘red‘], [‘eggs‘, ‘ham‘]],
           labels=[[0, 0, 0, 0, 0, 0, 0, 1, 0, 0], [1, 0, 0, 0, 0, 1, 0, 0, 1, 1]],
           names=[‘color‘, ‘food‘])

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In [309]:

df.query(‘color == "red"‘)

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In [310]:

# 如果多重索引没有命名 可以使用特殊的名字
df.index.names = [None, None]
df
df.query(‘ilevel_0 == "red"‘) # The convention is ilevel_0, which means “index level 0” for the 0th level of the index.

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# query() Use Cases 使用示例
# A use case for query() is when you have a collection of DataFrame objects
# that have a subset of column names (or index levels/names) in common.   ## 有公共列名称子集的df
# You can pass the same query to both frames
# without having to specify which frame you’re interested in querying.  ## 传入同样的query

In [311]:

df = pd.DataFrame(np.random.rand(n, 3), columns=list(‘abc‘))
df2 = pd.DataFrame(np.random.rand(n + 2, 3), columns=df.columns)
df
df2

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expr = ‘0.0 <= a <= c <= 0.5‘
mp = map(lambda frame: frame.query(expr), [df, df2])  # 同一个表达式，作用在有同样列名的多个df上

In [316]:

for i in mp:
    print(i)

          a         b         c
0  0.096087  0.799309  0.112070
7  0.431525  0.676385  0.458296
           a         b         c
10  0.029253  0.419409  0.051255

In [317]:

# query() Python versus pandas Syntax Comparison

# Full numpy-like syntax
df = pd.DataFrame(np.random.randint(n, size=(n, 3)), columns=list(‘abc‘))
df

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In [318]:

 df.query(‘(a < b) & (b < c)‘)
 df[(df.a < df.b) & (df.b < df.c)]

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# 几种其他的不同的写法
df.query(‘a < b & b < c‘)  # 去掉括号
df.query(‘a < b and b < c‘)  # 使用英文and
df.query(‘a < b < c‘)  # 连写，优雅的表达

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In [320]:

# The in and not in operators

# get all rows where columns "a" and "b" have overlapping values
# 得到a列和b列有重叠值的行，a列中的值在 in b列的值中
df = pd.DataFrame({‘a‘: list(‘aabbccddeeff‘), ‘b‘: list(‘aaaabbbbcccc‘),
                       ‘c‘: np.random.randint(5, size=12),
                       ‘d‘: np.random.randint(9, size=12)})
df

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df.query(‘a in b‘)  # 第一次运行113ms 第二次明显加快 25ms

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df[df.a.isin(df.b)]   # How you‘d do it in pure Python  仍然比query快 35ms

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df[~df.a.isin(df.b)]

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df.query(‘a not in b‘)

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In [328]:

# rows where cols a and b have overlapping values and col c‘s values are less than col d‘s
df.query(‘a in b and c < d‘)
df[df.a.isin(df.b) & (df.c < df.d)]

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# 注意：？？？？？
# Note that in and not in are evaluated in Python, since numexpr has no equivalent of this operation.
# However, only the in/not in expression itself is evaluated in vanilla Python.
# For example, in the expression
df.query(‘a in b + c + d‘)
# (b + c + d) is evaluated by numexpr and then the in operation is evaluated in plain Python. In general, any operations that can be evaluated using numexpr will be.

In [329]:

# Special use of the == operator with list objects
# 特别的用法，== 用于list
# Comparing a list of values to a column using ==/!= works similarly to in/not in
# 用==/!=比较列表的值与列的值，类似于in/not in
df

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df.query(‘b == ["a", "b", "c"]‘)  # b列中有列表中值的

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In [332]:

df.query(‘c == [1, 2]‘)
df.query(‘[1, 2] in c‘)
df[df.c.isin([1, 2])]

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# Boolean Operators 布尔操作符
# ~ 或 not
df = pd.DataFrame(np.random.rand(n, 3), columns=list(‘abc‘))
df
df[‘bools‘] = np.random.rand(len(df)) > 0.5
df

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df.query(‘~bools‘)
df.query(‘not bools‘)

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# 任意组合布尔表达式
shorter = df.query(‘a < b < c and (not bools) or bools > 2‘)  # short query syntax
longer = df[(df.a < df.b) & (df.b < df.c) & (~df.bools) | (df.bools > 2)]  # equivalent in pure Python
shorter
longer

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# Performance of query()
# DataFrame.query() using numexpr is slightly faster than Python for large frames
# Note : You will only see the performance benefits of using the numexpr engine with DataFrame.query()
# if your frame has more than approximately 200,000 rows

# query() 效能在大数据时高于数字表达式

In [ ]:

# Duplicate Data
# 识别和剔除重复数据，两个方法：duplicated and drop_duplicates，他们的参数都是列
# duplicated 返回布尔向量，标示重复的行
# drop_duplicates 删除重复列
# 默认保留第一个找到的值，但可以通过keep参数指定保留的值
# keep=‘first‘ (default): mark / drop duplicates except for the first occurrence. 只保留第一个
# keep=‘last‘: mark / drop duplicates except for the last occurrence. 只保留最后一个重复值
# keep=False: mark / drop all duplicates.  剔除所有重复值

In [336]:

df2 = pd.DataFrame({‘a‘: [‘one‘, ‘one‘, ‘two‘, ‘two‘, ‘two‘, ‘three‘, ‘four‘],
                    ‘b‘: [‘x‘, ‘y‘, ‘x‘, ‘y‘, ‘x‘, ‘x‘, ‘x‘],
                    ‘c‘: np.random.randn(7)})
df2

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