Python 如何转换数据帧

我有一个熊猫数据框，如下所示：-

import pandas as pd
import numpy as np
from datetime import datetime
start = datetime(2011, 1, 1)
end = datetime(2012, 1, 1)

index = pd.date_range(start, end)

Cols = ['Returns']



df = pd.DataFrame(abs(np.random.randn(366,1)), index=index, columns=Cols)

start1 = 2011
end1 = 2012

index1 = (start, end)
cols2=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']
df_out = pd.DataFrame(abs(np.random.randn(2,12)), index=index1, columns=cols2)

DFList = []
for group in df.groupby(df.index.month):
    DFList.append(group[1])


r2 = pd.concat([DFList[0], DFList[1] ,DFList[2], DFList[3], DFList[4], 
DFList[5],DFList[6],DFList[7],DFList[8], DFList[9], 
DFList[10],DFList[11]],ignore_index=True,axis=1)
cols2=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']
r2.columns=cols2

我需要以这样一种方式对它进行转换：索引是年，列是月。预期产出如下：-

import pandas as pd
import numpy as np
from datetime import datetime
start = datetime(2011, 1, 1)
end = datetime(2012, 1, 1)

index = pd.date_range(start, end)

Cols = ['Returns']



df = pd.DataFrame(abs(np.random.randn(366,1)), index=index, columns=Cols)

start1 = 2011
end1 = 2012

index1 = (start, end)
cols2=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']
df_out = pd.DataFrame(abs(np.random.randn(2,12)), index=index1, columns=cols2)

DFList = []
for group in df.groupby(df.index.month):
    DFList.append(group[1])


r2 = pd.concat([DFList[0], DFList[1] ,DFList[2], DFList[3], DFList[4], 
DFList[5],DFList[6],DFList[7],DFList[8], DFList[9], 
DFList[10],DFList[11]],ignore_index=True,axis=1)
cols2=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']
r2.columns=cols2

每年的单个值可以是总和或平均值。 我尝试了dataframe groupby，如下所示：-

import pandas as pd
import numpy as np
from datetime import datetime
start = datetime(2011, 1, 1)
end = datetime(2012, 1, 1)

index = pd.date_range(start, end)

Cols = ['Returns']



df = pd.DataFrame(abs(np.random.randn(366,1)), index=index, columns=Cols)

start1 = 2011
end1 = 2012

index1 = (start, end)
cols2=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']
df_out = pd.DataFrame(abs(np.random.randn(2,12)), index=index1, columns=cols2)

DFList = []
for group in df.groupby(df.index.month):
    DFList.append(group[1])


r2 = pd.concat([DFList[0], DFList[1] ,DFList[2], DFList[3], DFList[4], 
DFList[5],DFList[6],DFList[7],DFList[8], DFList[9], 
DFList[10],DFList[11]],ignore_index=True,axis=1)
cols2=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec']
r2.columns=cols2

我在这一点上感到困惑，无法继续下去。 提前感谢你。请建议前进的方向。

与一起使用指定聚合函数和 :

如果需要

month

以正确的顺序命名一个解决方案，其中包含已订购的和：

另一个解决方案是使用：