使用管道表达大 pandas 对接操作 [英] Expressing pandas subsetting operation using pipe

问题描述

有没有一种方法可以使用管道运算符来表达下面的pandas操作?

Is there a way I can express the pandas operations below using the pipe operator?

 df_a = df[df.index.year != 2000]
 df_b = df_a[(df_a['Month'].isin([3, 4, 5])) & (df_a['region'] == 'USA')]

推荐答案

不确定为什么要使用pipe进行此操作.

Not sure why would you want to use pipe for this operation.

pipe旨在通过一系列修改传入的DataFrame(

pipe is intended to make easier syntax for chained processing of DataFrame with a chain of functions that modify incoming DataFrame (see docs).

您要执行的操作是过滤带有多个过滤器(或蒙版)的DataFrame.

What you are trying to do is to filter DataFrame with a number of filters (or masks).

仅说明在此操作中使用pipe有点麻烦:

Just to illustrate that using pipe for this operation is somewhat cumbersome:

import pandas as pd
pd.np.random.seed(123)
# Generate some data
dates = pd.date_range('2014-01-01', '2015-12-31', freq='M')
df = pd.DataFrame({'region':pd.np.random.choice(['USA', 'Non-USA'], len(dates))}, index=dates)
df['Month'] = df.index.month
print df.head()

             region  Month
2014-01-31      USA      1
2014-02-28  Non-USA      2
2014-03-31      USA      3
2014-04-30      USA      4
2014-05-31      USA      5

您的原始过滤器会产生:

Your original filter would yield:

df_a = df[df.index.year != 2014]
df_b = df_a[(df_a['Month'].isin([3, 4, 5])) & (df_a['region'] == 'USA')]
print df_b

           region  Month
2015-03-31    USA      3
2015-05-31    USA      5    

以下是使用pipe获得相同输出的方法:

Here is how you could use pipe to get the same output:

def masker(df, mask):
    return df[mask]

mask1 = df.index.year != 2014
mask2 = df['Month'].isin([3, 4, 5])
mask3 = df['region'] == 'USA'

print df.pipe(masker, mask1).pipe(masker, mask2).pipe(masker, mask3)

           region  Month
2015-03-31    USA      3
2015-05-31    USA      5    

但是pandas能够以一种非常简单的方式(在这种情况下)处理过滤:

However pandas is able to process filtering in a rather simple (in this particular case) way:

print df[mask1 & mask2 & mask3]

           region  Month
2015-03-31    USA      3
2015-05-31    USA      5    

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