Question

我希望使用apply在其他列值的基础上在pandas数据框中创建新列。我收到此错误，但我不明白为什么：

File "C:\dev\Anaconda3\lib\site-packages\pandas\core\frame.py", line 2448, in _setitem_array
    raise ValueError('Columns must be same length as key')
ValueError: Columns must be same length as key

我误解了apply函数吗？您可以使用一个Apply调用来更新/创建多个列吗？

这是我的示例数据：

import pandas as pd

x = pd.DataFrame({'VP': ['Brian', 'Sarah', 'Sarah', 'Brian', 'Sarah'],
                  'Director': ['Jim', 'Ian', 'Ian', 'Jim', 'Jerry'],
                  'Requester': ['Kelly', 'Dave', 'Jordan', 'Matt', 'Rob'],
                  'VP from Query': ['Jordan', 'Justin', 'Sarah', 'Brian', 'Sarah'],
                  'Director from Query': ['Other', 'Other', 'Ian', 'Jim', 'Jerry'],
                  'Requester from Query': ['Kelly', 'Dave', 'Jordan', 'Matt', 'Rob']
                  })
x = x[['VP', 'Director', 'Requester', 'VP from Query', 'Director from Query', 'Requester from Query']]


def set_suggested_hierarchy(row):
    if row['VP'] != row['VP from Query']:
        return row[['VP', 'Director']]
    else:
        return row[['VP from Query', 'Director from Query']]


x[['Suggested VP', 'Suggested Director']] = x.apply(lambda row: set_suggested_hierarchy(row), axis=1)

非常感谢您

Answer 1

我在这里找到了答案：https://datascience.stackexchange.com/questions/29115/pandas-apply-return-must-have-equal-len-keys-and-value-when-setting-with-an-ite

基本上，我需要更改lambda函数以返回序列：

def set_suggested_hierarchy(row):
    if row['VP'] != row['VP from Query']:
        return pd.Series([row['VP'], row['Director']])
    else:
        return pd.Series([row['VP from Query'], row['Director from Query']])

Answer 2

一种解决方案是返回数据框的整个行，因为您正在将此函数应用于整个数据框：

def set_suggested_hierarchy(row):

    if row['VP'] != row['VP from Query']:
        row['Suggested VP'] = row['VP']
        row['Suggested Director'] = row['Director']
    else:
        row['Suggested VP'] = row['VP from Query']
        row['Suggested Director'] = row['Director from Query']

    return row

x = x.apply(lambda row: set_suggested_hierarchy(row), axis=1)

Answer 3

我认为您应该一起摆脱apply(axis=1)。看来您的逻辑可以实现为：

import numpy as np

x['Suggested VP'] = x.VP
x['Suggested Director'] = np.where(x.VP != x['VP from Query'], 
                                   x.Director, x['Director from Query'])

使用Apply在Pandas数据框中创建新列

3 个答案: