通过字典过滤熊猫数据帧

Question

我有一个有很多列的熊猫数据框。 （请参阅下表。）每列均属于组别分类G1-G4。组的映射在数据字典中。如果我想根据分组数据字典过滤熊猫数据框中的列，例如过滤掉所有G3并生成下面生成的表格，那么执行此操作的最有效方法是什么？

谢谢。

Answer 1

说数据帧是：

In [7]: df = pd.DataFrame({'T1': [1], 'T2': [2], 'T3': [3], 'T4': [4], 'T5': [5]}) 

In [8]: df 
Out[8]: 
    T1 T2 T3 T4 T5 
0 1 2 3 4 5 

并说过滤字典是：

In [9]: filter_dict = {'T1': 'G1', 'T2': 'G3', 'T3': 'G3', 'T4': 'G1', 'T5': 'G2'} 

您可以选择除了那些属于G3这样所有列：

In [6]: df[[col_name for col_name, group in filter_dict.items() if group != 'G3']] 
Out[6]: 
    T5 T4 T1 
0 5 4 1 

Answer 2

我迟到了派对，但这是另一种方式：

import pandas as pd 
import numpy as np 

filter_dict = {'T1': 'G1', 'T2': 'G3', 'T3': 'G3', 'T4': 'G1', 'T5': 'G2'} 

#some play data 
dta = np.random.rand(10,5) 
rows = pd.date_range('1-Jan-2001', periods=10) 
cols = ['T'+ str(x) for x in range(1,6)] 
df = pd.DataFrame(dta, rows, cols) 

''' 
        T1  T2  T3  T4  T5 
2001-01-01 0.981817 0.590287 0.421105 0.060628 0.007345 
2001-01-02 0.643111 0.813921 0.301809 0.414912 0.116028 
2001-01-03 0.366478 0.582521 0.997483 0.642552 0.662618 
2001-01-04 0.485125 0.062310 0.278239 0.838958 0.174067 
2001-01-05 0.953075 0.612431 0.204880 0.258736 0.551282 
2001-01-06 0.633442 0.852040 0.338404 0.137305 0.114481 
2001-01-07 0.828730 0.477185 0.456451 0.560955 0.713365 
2001-01-08 0.860316 0.809366 0.656306 0.728917 0.383045 
2001-01-09 0.492210 0.639744 0.511768 0.623203 0.495040 
2001-01-10 0.956224 0.188009 0.938048 0.999993 0.556607 
''' 

#convert wide to long cleanup the index and col names 
df1 = df.stack()\ 
     .reset_index()\ 
     .rename(columns={'level_0':'date','level_1':'ticker', 0:'val'})\ 
     .reset_index('date') 

#map ticker to group  
df1['grp'] = df1.ticker.map(filter_dict) 

#select stuff not in group 3 and pivot to wide format 
df1[df1.grp != 'G3'].pivot('date','ticker','val') 

''' 
ticker   T1  T4  T5 
date          
2001-01-01 0.981817 0.060628 0.007345 
2001-01-02 0.643111 0.414912 0.116028 
2001-01-03 0.366478 0.642552 0.662618 
2001-01-04 0.485125 0.838958 0.174067 
2001-01-05 0.953075 0.258736 0.551282 
2001-01-06 0.633442 0.137305 0.114481 
2001-01-07 0.828730 0.560955 0.713365 
2001-01-08 0.860316 0.728917 0.383045 
2001-01-09 0.492210 0.623203 0.495040 
2001-01-10 0.956224 0.999993 0.556607 
'''