对于循环，通过具有相同标头的目录中的csv文件进行解析，并在每个循环文件后打印新列

Question

对于循环，通过具有相同标头的目录中的csv文件进行解析，并在每个循环文件后打印新列

正如下面的代码所示，它将目录中的所有文件垂直合并。我希望它在每个文件后水平合并，以便有多行

import os
import pandas as pd
#RUN THIS AFTER MAKING ALL THE CSV FILEs
dfmaster = pd.DataFrame()
directory = "/content/drive/My Drive/"

for filename in os.listdir(directory):
    fullpath = os.path.join(directory, filename)
    if os.path.isfile(fullpath) and fullpath.endswith(".csv"):
        dfchild = pd.read_csv(fullpath)
        select_cols = ['var1', 'var2']
        #define columns you want to explort
        dfmaster = dfchild[select_cols]
        #####Problem here, After each file print to two new columns I don't know what to input here
    print(dfmaster.reset_index(drop=True))
    dfmaster.to_csv("/content/drive/My Drive/Subsurface_A.csv", index=False)

因此，总结：当前for循环垂直组合列。我想学习如何像在excel中那样水平执行此操作

而不是包含所有数据的A列和B列。我希望每个文件的列A B彼此相邻，以便有列A B C D E F G

抱歉，我不懂编码术语。如果国防部发现这一点，请在必要时重新措辞

谢谢

Answer 1

您可以在循环外部创建一个空df，然后沿每个循环的列连续连接：

#empty df
finaldf = pd.Dataframe()
for filename in os.listdir(directory):
    fullpath = os.path.join(directory, filename)
    if os.path.isfile(fullpath) and fullpath.endswith(".csv"):
        dfchild = pd.read_csv(fullpath)
        select_cols = ['obs', 'temperature']
        #define columns you want to explort
        dfmaster = dfchild[select_cols]

        #new line
        finaldf = pd.concat([finaldf, dfmaster],axis = 1)


    print(finaldf.reset_index(drop=True))
    finaldf.to_csv("/content/drive/My Drive/Subsurface_A.csv", index=False)