pandas 为索引使用多列旋转 DataFrame
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Pivoting DataFrame with multiple columns for the index
提问by ProgSky
I have a dataframe and I want to transpose only few rows to column.
我有一个数据框，我只想将几行转为列。
This is what I have now.
这就是我现在所拥有的。
Entity Name Date Value
0 111 Name1 2018-03-31 100
1 111 Name2 2018-02-28 200
2 222 Name3 2018-02-28 1000
3 333 Name1 2018-01-31 2000
I want to create date as the column and then add value. Something like this:
我想创建日期作为列，然后添加值。像这样的东西：
Entity Name 2018-01-31 2018-02-28 2018-03-31
0 111 Name1 NaN NaN 100.0
1 111 Name2 NaN 200.0 NaN
2 222 Name3 NaN 1000.0 NaN
3 333 Name1 2000.0 NaN NaN
I can have identical Namefor two different Entitys. Here is an updated dataset.
Name对于两个不同的Entitys，我可以有相同的。这是一个更新的数据集。
Code:
代码：
import pandas as pd
import datetime
data1 = {
'Entity': [111,111,222,333],
'Name': ['Name1','Name2', 'Name3','Name1'],
'Date': [datetime.date(2018,3, 31), datetime.date(2018,2,28), datetime.date(2018,2,28), datetime.date(2018,1,31)],
'Value': [100,200,1000,2000]
}
df1 = pd.DataFrame(data1, columns= ['Entity','Name','Date', 'Value'])
How do I achieve this? Any pointers? Thanks all.
我如何实现这一目标？任何指针？谢谢大家。
回答by cs95
Based on your update, you'd need pivot_tablewith two index columns -
根据您的更新，您需要pivot_table两个索引列 -
v = df1.pivot_table(
index=['Entity', 'Name'],
columns='Date',
values='Value'
).reset_index()
v.index.name = v.columns.name = None
v
Entity Name 2018-01-31 2018-02-28 2018-03-31
0 111 Name1 NaN NaN 100.0
1 111 Name2 NaN 200.0 NaN
2 222 Name3 NaN 1000.0 NaN
3 333 Name1 2000.0 NaN NaN
回答by YOBEN_S
From unstack
从 unstack
df1.set_index(['Entity','Name','Date']).Value.unstack().reset_index()
Date Entity Name 2018-01-31 00:00:00 2018-02-28 00:00:00 \
0 111 Name1 NaN NaN
1 111 Name2 NaN 200.0
2 222 Name3 NaN 1000.0
3 333 Name1 2000.0 NaN
Date 2018-03-31 00:00:00
0 100.0
1 NaN
2 NaN
3 NaN
