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使用字典映射数据帧索引

[英]Map dataframe index using dictionary

Why doesn't df.index.map(dict) work like df['column_name'].map(dict) ? 为什么df.index.map(dict)不能像df['column_name'].map(dict)那样工作df.index.map(dict) df['column_name'].map(dict)

Here's a little example of trying to use index.map: 这是尝试使用index.map的一个小例子:

import pandas as pd

df = pd.DataFrame({'one': {'A': 10, 'B': 20, 'C': 30, 'D': 40, 'E': 50}})
map_dict = {'A': 'every', 'B': 'good', 'C': 'boy', 'D': 'does', 'E': 'fine'}
df
'''
    one
A   10
B   20
C   30
D   40
E   50
'''

df['two'] = df.index.map(mapper=map_dict)

This raises TypeError: 'dict' object is not callable 这引发了TypeError: 'dict' object is not callable

Feeding it a lambda works: 喂它一个lambda工作:

df['two'] = df.index.map(mapper=(lambda x: map_dict[x])); df
'''
   one    two
A   10  every
B   20   good
C   30    boy
D   40   does
E   50   fine
'''

However, resetting the index and mapping on a column works as expected without complaint: 但是,重置索引和列上的映射可以按预期工作而无需投诉:

df.reset_index(inplace=True)
df.rename(columns={'index': 'old_ndx'}, inplace=True) #so there's no index name confusion
df['two'] = df.old_ndx.map(map_dict); df

'''
  old_ndx  one    two
0       A   10  every
1       B   20   good
2       C   30    boy
3       D   40   does
4       E   50   fine
'''

I'm not answering your question... Just giving you a better work around. 我没有回答你的问题......只是给你一个更好的解决方法。
Use to_series() them map 使用to_series() map它们

df = pd.DataFrame({'one': {'A': 10, 'B': 20, 'C': 30, 'D': 40, 'E': 50}})
map_dict = {'A': 'every', 'B': 'good', 'C': 'boy', 'D': 'does', 'E': 'fine'}

df['two'] = df.index.to_series().map(map_dict)

df

   one    two
A   10  every
B   20   good
C   30    boy
D   40   does
E   50   fine

Adding get at the end 最后添加get

df['Two']=df.index.map(map_dict.get)
df
Out[155]: 
   one    Two
A   10  every
B   20   good
C   30    boy
D   40   does
E   50   fine

An alternative workaround to calling map: 调用map的另一种解决方法:

df['two'] = pd.Series(map_dict)

df

   one    two
A   10  every
B   20   good
C   30    boy
D   40   does
E   50   fine

In any case, until the mapping issue gets resolved (per juanpa.arrivillaga's comment) you have to convert either the index or the dict-to-map to a pandas Series. 在任何情况下,直到映射问题得到解决(根据juanpa.arrivillaga的评论),你必须将索引或dict-to-map转换为pandas系列。

As of pandas version 0.23.x (released at May 15th, 2018) this problem is fixed: 截至pandas版本0.23.x(2018年5月15日发布),此问题已修复:

import pandas as pd
pd.__version__        # 0.23.4

df = pd.DataFrame({'one': {'A': 10, 'B': 20, 'C': 30, 'D': 40, 'E': 50}})
map_dict = {'A': 'every', 'B': 'good', 'C': 'boy', 'D': 'does', 'E': 'fine'}
df
#    one
# A   10
# B   20
# C   30
# D   40
# E   50
df.index.map(map_dict)
#        one
# every   10
# good    20
# boy     30
# does    40
# fine    50

From the What's New page for pandas 0.23.0 it says: 从Pandas 0.23.0的What's New页面中可以看出:

Index.map() can now accept Series and dictionary input objects (GH12756, GH18482, GH18509). Index.map()现在可以接受系列和字典输入对象(GH12756,GH18482,GH18509)。

For more information, check the help page of Index.map 有关更多信息,请查看Index.map的帮助页面

map (a python keyword) is apparently being used as a method of df.index map (一个python关键字)显然被用作df.index的方法

Because this has its own internal demands, passing it an argument which has no __call__ method is not allowed. 因为它有自己的内部需求,所以不允许传递没有__call__方法的参数。

lambda and functions are callable, a simple test: lambda和函数是可调用的,一个简单的测试:

def foo():
    pass
if foo.__call__:
    print True
# Prints True

bar = lambda x: x+1
if bar.__call__:
    print True
# Prints True

print {'1':'one'}.__call__
# AttributeError: 'dict' object has no attribute '__call__'

一个较短的替代方案 - 没有明确调用to_seriespd.Series

df['two'] = df.rename(map_dict).index

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