读取多个CSV文件并将其水平合并 [英] Reading multiple CSV files and joining them horizontally

问题描述

我有几个csv格式的文件，例如100-age.csv 100-rel.csv 100-gender.csv 101-age.csv ... 101-gender.csv ... 482-rel.csv 482-gender.csv等.我必须为每个索引(例如100-combo.csv)创建新文件，该索引将同时连接100-age.csv 100-rel.csv和100-gender.csv .我可以使用熊猫对一个文件执行此操作

I have a couple of files in csv format like 100-age.csv 100-rel.csv 100-gender.csv 101-age.csv ... 101-gender.csv ... 482-rel.csv 482-gender.csv etc. I have to make new file for every index i.e. 100-combo.csv which which will join 100-age.csv 100-rel.csv and 100-gender.csv horizontally. I could do this for one file using pandas

import pandas as pd

age = pd.read_csv('100-age.csv', header=None)
gender = pd.read_csv('100-gender.csv', header=None)
rel = pd.read_csv('100-rel.csv', header=None)

combined = pd.concat([age, gender, rel], axis=1)

combined.to_csv('100-combo.csv', header=None, index=None)

使用linux，有一些像cat这样的方法只能垂直添加，即彼此堆叠，而paste命令会干扰我在这些文件中的格式.

Using linux, there are methods like cat which only add vertically, i.e. stacking on top of each other and paste command which disturbs the formatting that I have in these files.

    def merged_data(i):   

        age = pd.read_csv(path+str(i)+'.pdf-age.csv', header=None, error_bad_lines=False)
        gender = pd.read_csv(path+str(i)+'.pdf-gender.csv', header=None, error_bad_lines=False)
        rel = pd.read_csv(path+str(i)+'.pdf-rel.csv', header=None, error_bad_lines=False)
        combined = pd.concat([age, gender, rel], axis=1)
        combined['block'] = str(i)
        combined.to_csv(path+str(i)+'-combo.csv', header=None, index=None)

for num in range(1,483):

    merged_data(num)

我收到此错误

EmptyDataError: No columns to parse from file

但是，我知道我所有的数据文件都具有某些或其他值

But, I know that all my data files have some or other values

推荐答案

我做到了，得到了我想要的.我用

I did this and got what I wanted. I used

import pandas as pd
import numpy as np
from pandas.io.common import EmptyDataError

    def merged_data(i):   
        try:
            age = pd.read_csv(path+str(i)+'.pdf-age.csv', header=None, error_bad_lines=False, delim_whitespace=True)
        except EmptyDataError:
            age = pd.DataFrame()
        try:  
            gender = pd.read_csv(path+str(i)+'.pdf-gender.csv', header=None, error_bad_lines=False, delim_whitespace=True)
        except EmptyDataError:
            gender = pd.DataFrame()
        try:
            rel = pd.read_csv(path+str(i)+'.pdf-rel.csv', header=None, error_bad_lines=False, delim_whitespace=True)
        except EmptyDataError:
            rel = pd.DataFrame()
            combined = pd.concat([age, gender, rel], axis=1)
            combined['block'] = str(i)
            combined.to_csv(path+str(i)+'-combo.csv', header=None, index=None)

for num in range(1,483):

    merged_data(num)

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