熊猫 - 索引类型值的更改

我正在使用multiIndex熊猫数据框。我的指数值以字符串形式报告 - 但是，我需要将它们更改为整数或浮点数，以便随后对它们进行一些计算。有没有一种有效的方法来做到这一点（最好是没有for循环，因为那些耗费大量的计算时间）？熊猫 - 索引类型值的更改

import pandas as pd 
import numpy as np 

idx = pd.IndexSlice 
ix = pd.MultiIndex.from_product(
    [['2015', '2016', '2017', '2018'], 
    ['2016', '2017', '2018', '2019', '2020'], 
    ['A', 'B', 'C']], 
    names=['SimulationStart', 'ProjectionPeriod', 'Group'] 
) 

df = pd.DataFrame(np.random.randn(60, 1), index=ix, columns=['Origin']) 
origin = df.loc[idx[:, :, :], 'Origin'].values 


get_index_values = df.index.get_level_values 
projection = get_index_values('ProjectionPeriod') 

# This function fails - is there an easy solution for this 
# (preferably without accessing each item at a time in a for loops)? 
int(projection)

来源

2016-11-04 Andreas

对不起你'后df.index.set_levels（projection.astype（INT），水平='ProjectionPeriod '，inplace = True）'？ – EdChum

@EdChum：谢谢你的回答 - 'astype（int）'解决了问题 – Andreas

使用astype转换的dtype和set_levels设置特定指数的水平值：

In [15]: 
df.index.set_levels(projection.astype(int), level='ProjectionPeriod', inplace=True) 
df.index.get_level_values('ProjectionPeriod') 

Out[15]: 
Int64Index([2016, 2016, 2016, 2016, 2016, 2016, 2016, 2016, 2016, 2017, 2017, 
      2017, 2017, 2017, 2017, 2016, 2016, 2016, 2016, 2016, 2016, 2016, 
      2016, 2016, 2017, 2017, 2017, 2017, 2017, 2017, 2016, 2016, 2016, 
      2016, 2016, 2016, 2016, 2016, 2016, 2017, 2017, 2017, 2017, 2017, 
      2017, 2016, 2016, 2016, 2016, 2016, 2016, 2016, 2016, 2016, 2017, 
      2017, 2017, 2017, 2017, 2017], 
      dtype='int64', name='ProjectionPeriod')

来源

2016-11-07 13:13:05 EdChum

熊猫 - 索引类型值的更改

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