read_excel('path_to_excel_file.xlsx', sheet_name='sheet_name') # 修改数据 df['Column1'] = df['Column1'] + 10 # 将修改后的数据保存回工作表 with pd.ExcelWriter('path_to_excel_file.xlsx', engine='openpyxl') as writer: writer.book = workbook df.to_excel(writer, sheet_name='...
import pandas as pd def test(): # 读取Excel文件 df = pd.read_excel('测试数据.xlsx') def modify_value(x): if x < 5: return '是' elif x < 10: return '否' else: return 'x' # 插入列 for col_num in range(4, 9): df.insert(loc=col_num, column=f'列{col_num-3}', value...
# Modify a Column Name columnsNamesArr[0] = 'Test' indexNamesArr = df.index.values print(indexNamesArr) indexNamesArr[0] = 2 print(df) #df1 = df.groupby('userId')['rating'].agg(['count','mean']).reset_index() df1 = pd.read_excel(excel_file) # print(df1[['休息食事时间合计...
# -*- coding: utf-8 -*- """ File Name: modify_excel Description : Author : Json date: 2020/11/27 Change Activity: 2020/11/27: """ import pandas as pd from pandas import DataFrame from dateutil.parser import parse from pandas import to_datetime from datetime import datetime from open...
_excel(LakeHouseFilePath, engine='openpyxl', sheet_name=0, header=None, skiprows=0, usecols='B,C,D', dtype={'B:str','C:np.float32','D:np.float32'}, na_filter=False) 48 display(PandasDataFrame) 49 bork File ~/cluster-env/trident_env/lib/python3.10/site-packages/pandas/io/excel/...
在pandas DataFrame中添加多个列名可以通过以下几种方式实现: 1. 使用列表赋值:可以通过将一个包含多个列名的列表赋值给DataFrame的columns属性来添加多个列名。例如: ...
2.1 读取excel数据 file = request.files.get("file") read_ex = pd.read_excel(file) df = pd.DataFrame(read_ex) 1.获取列标题: columns = df.columns.values.tolist() 2.获取某一列数据: area_list = df['大区'].tolist() # 获取列标题为“大区”的列数据 ...
# Modify a Column Name columnsNamesArr[0] = 'Test' indexNamesArr = df.index.values print(indexNamesArr) indexNamesArr[0] = 2 print(df) #df1 = df.groupby('userId')['rating'].agg(['count','mean']).reset_index() df1 = pd.read_excel(excel_file) ...
T.modify(5,"aaa":NAME,1000:SALARY) SPL直接提供了修改函数,符合初学者的常识。当然,SPL也可以取出记录再修改,两种方法各自适合不同的场景。 在指定位置插入新记录。Pandas: record=pd.DataFrame([[100,"wang","lao","Femal","CA", pd.to_datetime("1999-01-01"), pd.to_datetime("2009-03-04"),"...
logging.basicConfig(filename='data_operations.log',level=logging.INFO)defread_data(file_path):logging.info(f"User{user_name}is reading data from{file_path}")df=pd.read_csv(file_path)returndfdefmodify_data(df,column,value):logging.info(f"User{user_name}is modifying column{column}with value...