如何为数据框中的每一列创建一个csv文件? [英] How to create a csv file for each column in a dataframe?

问题描述

我在VSCode中使用Python.我读取了一个CSV文件，并将其转换为用于股票市场收盘价的数据框.第一列是日期列，其他各是股票代码的收盘价.我想将具有多个列的数据框拆分为单独的.csv文件.每个新的.csv文件将按照每个股票代码列标题的名称来命名.

I am using Python in VSCode. I read a CSV file and transformed it in a dataframe for stock market's close prices. First column is date column and others are each stock symbol close prices. I would like to split this dataframe with multiple columns into separate .csv files. Each new .csv file will be named as per each stock symbol column´s header´s name.

下面是数据框的链接作为示例(原始文件具有500个coluns和10,000行):

Below is a link for the dataframe as example (the original file has like 500 coluns and 10,000 rows):

因此，每个新的.csv文件都将被命名为"TAEE11.csv" ，依此类推，在该列下包含相应的值，并保留"Date".每个文件的列.我想将这些新创建的.csv文件保存到新文件夹(例如，当您在VSCode中使用Python时，可以使用 *.to_csv 将这些新的.csv文件保存到新文件夹)./p>

So, each new .csv file will be named such as "TAEE11.csv" and so on contain the respective values down that column keeping the "Date" column for each file as well. I would like to save these newly created .csv files to a new folder (like when you are using Python inside VSCode you can save these new .csv files to a new folder with *.to_csv).

推荐答案

• 因为您已经有一个数据框
• 将数据框的索引设置为日期" 列
• 遍历每列并将其保存到csv.
  • 使用 df [col]
  为每一列选择数据
  • csv文件名将为 f'{col} .csv'，其中 col 是列名.
  • Since you already have a dataframe
  • Set the index of the dataframe as the 'Date' column
  • Iterate through each column and save it to a csv.
    • Select the data for each column with df[col]
    • The csv file name will be f'{col}.csv', where col is the column name.
    • df.to_csv(os.getcwd()+'\\ file.csv')进入 AppData 文件夹
    • 当前工作目录不一定是您想要保存文件的位置.
    • 指定完整的所需保存路径，例如'c:/Users/<< user_name>>/Documents/{col} .csv'.
    • df.to_csv(os.getcwd()+'\\file.csv') goes into the AppData folder
    • The current working directory is not necessarily where you want the file saved.
    • Specify the full desired save path, 'c:/Users/<<user_name>>/Documents/{col}.csv', for example.

    import pandas as pd
    
    # set Date as the index
    df.set_index('Date', inplace=True)
    
    # iterate through each column and save it
    for col in df.columns:
        df[col].to_csv(f'c:/Users/<<user_name>>/Documents/{col}.csv', index=True)
    

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