- 读取数据
import pandas as pd
import collections
def readLocationCodeForExcel():
read_file = r"test.xlsx"
sheet_names = {"库位码","地堆码"}
sheet_data = pd.ExcelFile(read_file) #读取sheet数据
#sheet列表
read_sheet_data = sheet_data.sheet_names
#查看缺少的sheet
lack_set = sheet_names - set(read_sheet_data)
#初始化数组
read_code_array = np.array([])
row_col_array = np.array([])
region_array = np.array([])
if lack_set:
logger.info("缺少的sheet将不会查询:{}".format(lack_set))
sheet_names = sheet_names - lack_set
for sheet_name in sheet_names:
df = pd.read_excel(read_file,sheet_name=sheet_name,dtype=str)
if sheet_name in df.keys():
#print(type(df[sheet_name].values))
#read_code_list = read_code_list + list(df[sheet_name].values)
read_code_array = np.hstack((read_code_array,df[sheet_name].values))# 读取 地堆 列 水平组合 有点像字符组合 str1=str1+strx
row_col_array = np.hstack((row_col_array,df["位置"].values))
region_array = np.hstack((region_array,df["区域名称"].values))
return read_code_array, row_col_array,region_array
- 写入数据
import pandas as pd
import collections
def wirteInventoryDataToExcelTest(data):
write_file = "path_to_file.xlsx"
#data = (1,2,3)
df = pd.DataFrame(data)
writer = pd.ExcelWriter(write_file)
df.to_excel(writer,index=False,startrow=0) # index=False不写入序号
#df1.to_excel(writer)
writer.save()
#region_array2 等 为 np.array([....]) 数据 其中 region_array2[0] 存的是excel表头,前天数组同样
data_dict = collections.OrderedDict() #把字典变为有序字典 用于写入excel数据有顺序写入
data_dict[region_array2[0]] = np.delete(region_array2, 0)
data_dict[row_col_array2[0]] = np.delete(row_col_array2, 0)
data_dict[locationCode_array[0]] = np.delete(locationCode_array,0)
data_dict[identifyCode_array[0]] = np.delete(identifyCode_array, 0)
data_dict[p_qty_array[0]] = np.delete(p_qty_array, 0)
data_dict[unitName_array[0]] = np.delete(unitName_array, 0)
data_dict[p_name_array[0]] = np.delete(p_name_array, 0)
data_dict[sellAttributeValues_array[0]] = np.delete(sellAttributeValues_array, 0)
wirteInventoryDataToExcelTest(data_dict)
原文地址:https://www.cnblogs.com/wanderingfish/p/11175322.html
时间: 2024-10-07 22:20:48