如何计算 pandas 中重新采样的多索引数据框 [英] How can I count a resampled multi-indexed dataframe in pandas

问题描述

我发现了如何对多索引重新采样的描述:

I found this description of how to resample a multi-index:

在熊猫MultiIndex内重新采样

但是，一旦我使用count而不是sum，该解决方案就不再起作用

However as soon as I use count instead of sum the solution is not working any longer

这可能与以下内容有关:使用"how = count"引起问题的重新采样

This might be related to: Resampling with 'how=count' causing problems

不起作用的计数和字符串:

values_a =[1]*16
states = ['Georgia']*8 + ['Alabama']*8
#cities = ['Atlanta']*4 + ['Savanna']*4 + ['Mobile']*4 + ['Montgomery']*4
dates = pd.DatetimeIndex([datetime.datetime(2012,1,1)+datetime.timedelta(days = i) for i in range(4)]*4)
df2 = pd.DataFrame(
    {'value_a': values_a},
    index = [states, dates])
df2.index.names = ['State', 'Date']
df2.reset_index(level=[0], inplace=True)
print(df2.groupby(['State']).resample('W',how='count'))

收益:

         2012-01-01           2012-01-08         
              State  value_a       State  value_a
State                                            
Alabama           2        2           6        6
Georgia           2        2           6        6

以 sum 和数字作为值的工作版本

values_a =[1]*16
states = ['Georgia']*8 + ['Alabama']*8
#cities = ['Atlanta']*4 + ['Savanna']*4 + ['Mobile']*4 + ['Montgomery']*4
dates = pd.DatetimeIndex([datetime.datetime(2012,1,1)+datetime.timedelta(days = i) for i in range(4)]*4)
df2 = pd.DataFrame(
    {'value_a': values_a},
    index = [states, dates])
df2.index.names = ['State', 'Date']
df2.reset_index(level=[0], inplace=True)
print(df2.groupby(['State']).resample('W',how='sum'))

收益率(注意不要重复州"):

Yields (notice no duplication of 'State'):

                    value_a
State   Date               
Alabama 2012-01-01        2
        2012-01-08        6
Georgia 2012-01-01        2
        2012-01-08        6

推荐答案

使用count时，状态不是令人讨厌的列(它可以计算字符串)，所以resample将对其应用计数(尽管输出不是我所期望的).您可以执行类似的操作(告诉它仅将count应用于value_a)，

When using count, state isn't a nuisance column (it can count strings) so the resample is going to apply count to it (although the output is not what I would expect). You could do something like (tell it only to apply count to value_a),

>>> print df2.groupby(['State']).resample('W',how={'value_a':'count'})

                    value_a
State   Date               
Alabama 2012-01-01        2
        2012-01-08        6
Georgia 2012-01-01        2
        2012-01-08        6

或更笼统地说，您可以将不同种类的how应用于不同的列:

Or more generally, you can apply different kinds of how to different columns:

>>> print df2.groupby(['State']).resample('W',how={'value_a':'count','State':'last'})

                      State  value_a
State   Date                        
Alabama 2012-01-01  Alabama        2
        2012-01-08  Alabama        6
Georgia 2012-01-01  Georgia        2
        2012-01-08  Georgia        6

因此，尽管以上内容使您可以count重新采样的多索引数据帧，但并不能解释how='count'的输出行为.以下更接近我期望的行为方式:

So while the above allows you to count a resampled multi-index dataframe it doesn't explain the behavior of output fromhow='count'. The following is closer to the way I would expect it to behave:

print df2.groupby(['State']).resample('W',how={'value_a':'count','State':'count'})

                   State  value_a
State   Date                      
Alabama 2012-01-01      2        2
        2012-01-08      6        6
Georgia 2012-01-01      2        2
        2012-01-08      6        6

这篇关于如何计算 pandas 中重新采样的多索引数据框的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！