将多个csv文件导入pandas并连接成一个DataFrame

问题描述

我想从一个目录中读取几个 csv 文件到 Pandas 中，并将它们连接成一个大的 DataFrame.我一直无法弄清楚.这是我目前所拥有的:

I would like to read several csv files from a directory into pandas and concatenate them into one big DataFrame. I have not been able to figure it out though. Here is what I have so far:

import glob
import pandas as pd

# get data file names
path =r'C:DRODCL_rawdata_files'
filenames = glob.glob(path + "/*.csv")

dfs = []
for filename in filenames:
    dfs.append(pd.read_csv(filename))

# Concatenate all data into one DataFrame
big_frame = pd.concat(dfs, ignore_index=True)

我想我在 for 循环中需要一些帮助???

I guess I need some help within the for loop???

推荐答案

如果您的所有 csv 文件中的列都相同，那么您可以尝试以下代码.我添加了 header=0 以便在阅读 csv 后可以将第一行指定为列名.

If you have same columns in all your csv files then you can try the code below.I have added header=0 so that after reading csv first row can be assigned as the column names.

import pandas as pd
import glob

path = r'C:DRODCL_rawdata_files' # use your path
all_files = glob.glob(path + "/*.csv")

li = []

for filename in all_files:
    df = pd.read_csv(filename, index_col=None, header=0)
    li.append(df)

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

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