Question

我位于一个包含36个不同文件夹的目录中。每个文件夹中都有一个单独的csv。我想将所有这些附加在一起，以在python中制作一个大数据框。

在R中，我会这样做：

cwd = getwd() #get current directory
fil = list.files() #get list of all files/folders in the directory
Bigdf = NULL #initialize empty df
for(i in fil){ #read through all folders in current directory
    setwd(paste0(cwd,'/',i)) #navigate to i'th folder
    fil2 = list.files() #get list of files in i'th folder
    for(j in fil2){
        a = read.csv(paste0(cwd,'/',i,'/',j)) #read in all csv's 
        Bigdf = rbind(Bigdf,a[,c(2,4:11)]) #append desired columns to data frame
    }
    setwd(cwd) 
}

我该如何在python中做类似的事情？

我尝试实现How can I read the contents of all the files in a directory with pandas?和How do I list all files of a directory?，但无济于事。我想我缺少明显的东西，希望有人能指出我正确的方向。

Answer 1

import glob
import pandas as pd

li =[]

for filename in glob.iglob('src/**/*.csv', recursive=True):
    df = pd.read_csv(filename, index_col=None, header=0)
    li.append(df)

frame = pd.concat(li, axis=0, ignore_index=True)

组合

Import multiple csv files into pandas and concatenate into one DataFrame

和

How to use glob() to find files recursively?

从子目录导航并追加csv

1 个答案: