Question

我正在尝试从三个父（或源）数据框（每个从.csv文件创建）创建一个数据框，但是当将结果数据框写入文件或在屏幕上打印时，名为“index”的列将显示出来。如何抑制/删除它们？

三个“父”数据框：

df1 ...
   fname  lname employer  score1  score2  score3
0  Alice  Adams      IMB    -1.0     2.5    -0.2
1  Alice  Brown      MFS     2.2    -7.9     3.7
2  Alice   Curt      OCR     2.6    -1.2    -0.7

df2 ...
   fname  lname employer  score1  score2  score3
0  Alice  Adams      IMB     3.0     0.1    -2.9
1  Alice  Brown      MFS    -2.1     2.6    -1.0
2  Alice   Curt      OCR     3.1     1.9    -0.1

df3 ...
   fname  lname employer  score1  score2  score3
0  Alice  Adams      IMB    -1.0    -2.1     0.1
1  Alice  Brown      MFS     3.2    -0.9     5.1
2  Alice   Curt      OCR    -1.1    -1.2    -1.9

经过一系列的操作，我得到了这个：

   fname  lname  index employer  score1  index employer  score3  index employer  score1  index employer  score3  index employer  score1  index employer  score3
0  Alice  Adams      0      IMB    -1.0      2      OCR    -0.7      1      MFS    -2.1      0      IMB    -2.9      2      OCR    -1.1      2      OCR    -1.9
1  Alice  Brown      1      MFS     2.2      0      IMB    -0.2      0      IMB     3.0      1      MFS    -1.0      0      IMB    -1.0      0      IMB     0.1
2  Alice   Curt      2      OCR     2.6      1      MFS     3.7      2      OCR     3.1      2      OCR    -0.1      1      MFS     3.2      1      MFS     5.1

我在寻找什么：
删除名为“index”的列。

我有一个MWE，我粘贴了上面的结果。如果您想在此处查看源.csv和.py文件，请与我们联系。

附录
发布源.csv文件和.py脚本：

A.csv ...  
fname,lname,employer,score1,score2,score3
Alice,Adams,IMB,-1.0,2.5,-0.2
Alice,Brown,MFS,2.2,-7.9,3.7
Alice,Curt,OCR,2.6,-1.2,-0.7

B.csv ...
fname,lname,employer,score1,score2,score3
Alice,Adams,IMB,3.0,0.1,-2.9
Alice,Brown,MFS,-2.1,2.6,-1.0
Alice,Curt,OCR,3.1,1.9,-0.1

C.csv ...
fname,lname,employer,score1,score2,score3
Alice,Adams,IMB,-1.0,-2.1,0.1
Alice,Brown,MFS,3.2,-0.9,5.1
Alice,Curt,OCR,-1.1,-1.2,-1.9

现在，.py脚本......

# -*- coding: utf-8 -*-

import fnmatch
import os
import matplotlib.pyplot as plt
import pandas as pd

pd.set_option('display.max_columns', None)

Datasets = ['A', 'B', 'C']
bigDF = pd.DataFrame()

for fname in Datasets:
    if fname == 'A':
        csvdf = pd.read_csv(fname+'.csv')
        csvdfBUa = csvdf[['fname', 'lname']]
        csvdfBUb = csvdf[['employer', 'score1']]
        csvdfBUb = csvdfBUb.sort(['score1'], ascending=[1])
        csvdfBUb = csvdfBUb.reset_index()
        csvdfBUc = csvdf[['employer', 'score3']]
        csvdfBUc = csvdfBUc.sort(['score3'], ascending=[1])
        csvdfBUc = csvdfBUc.reset_index()
        csvdfBU = pd.concat([csvdfBUa, csvdfBUb, csvdfBUc], axis=1, ignore_index=False)
        print csvdf
        if len(bigDF.index) < 1:
            bigDF = csvdfBU
        else:
            bigDF = pd.concat([bigDF, csvdfBU], axis=1, ignore_index=False)
    elif fname == 'B':
        csvdf = pd.read_csv(fname+'.csv')
        csvdfAFb = csvdf[['employer', 'score1']]
        csvdfAFb = csvdfAFb.sort(['score1'], ascending=[1])
        csvdfAFb = csvdfAFb.reset_index()
        csvdfAFc = csvdf[['employer', 'score3']]
        csvdfAFc = csvdfAFc.sort(['score3'], ascending=[1])
        csvdfAFc = csvdfAFc.reset_index()
        csvdfAF = pd.concat([csvdfAFb, csvdfAFc], axis=1, ignore_index=False)
        print csvdf
        if len(bigDF.index) < 1:
            bigDF = csvdfAF
        else:
            bigDF = pd.concat([bigDF, csvdfAF], axis=1, ignore_index=False)
    elif fname == 'C':
        csvdf = pd.read_csv(fname+'.csv')
        csvdfGAb = csvdf[['employer', 'score1']]
        csvdfGAb = csvdfGAb.sort(['score1'], ascending=[1])
        csvdfGAb = csvdfGAb.reset_index()
        csvdfGAc = csvdf[['employer', 'score3']]
        csvdfGAc = csvdfGAc.sort(['score3'], ascending=[1])
        csvdfGAc = csvdfGAc.reset_index()
        csvdfGA = pd.concat([csvdfGAb, csvdfGAc], axis=1, ignore_index=False)
        print csvdf
        if len(bigDF.index) < 1:
            bigDF = csvdfGA
        else:
            bigDF = pd.concat([bigDF, csvdfGA], axis=1, ignore_index=False)

print bigDF

Answer 1

您可以使用以下方法删除“索引”列：

del df['index']

注意：我怀疑你可以在第一时间避免这种情况......

Answer 2

import numpy as np
import pandas as pd
df[np.negative(pd.Series(df.columns).str.contains('index'))]

从Pandas数据帧中抑制或删除名为“index”的列

2 个答案: