python - 如何将函数应用于 Pandas 系列中的每一行？

Question

我有一个只有一列的表格。我想将我编写的函数应用到系列中的每一行。但是，当我这样做时出现错误!

The table looks like this:        And I want to get this:
names                             names
bank account                      bank account|bank|account
1256864                           1256864
bank share                        bank share|bank|share
42,566                            42,566          
bank currency                     bank currency|bank|currency
Dollar                            Dollar
batch number                      batch number|batch|number
001444                            001444
...                                ...
                    

这是我写的代码:

import pandas as pd
import re


df = pd.read_table('list_a.tsv')

def sep_rows (text):
    sperated = '|'.join(re.split(r'\s+', text))
    return text+'|'+sperated

# this applies the function to ALL rows!
print(df['names'].apply(sep_rows))
# I tried to choose every other row
a = df.iloc[::2].apply(sep_rows)

print(a) # But I gen an error!

我明白了:

TypeError: expected string or bytes-like object

Answer 1

您的方法(使用 re 和 apply)过于复杂且缓慢。以下表达式使用原生 Pandas 向量化，效率更高(运行速度大约快 4 倍)。

evens = df['names'].iloc[::2]    
evens[:] = evens + '|' + evens.str.replace('\s+', '|')
#                       names
#0  bank account|bank|account
#1                    1256864
#2      bank share|bank|share
#3                     42,566