如何在 Pandas 数据框中展开一列
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How to spread a column in a Pandas data frame
提问by neversaint
I have the following pandas data frame:
我有以下Pandas数据框：
import pandas as pd
import numpy as np
df = pd.DataFrame({
'fc': [100,100,112,1.3,14,125],
'sample_id': ['S1','S1','S1','S2','S2','S2'],
'gene_symbol': ['a', 'b', 'c', 'a', 'b', 'c'],
})
df = df[['gene_symbol', 'sample_id', 'fc']]
df
Which produces this:
产生这个：
Out[11]:
gene_symbol sample_id fc
0 a S1 100.0
1 b S1 100.0
2 c S1 112.0
3 a S2 1.3
4 b S2 14.0
5 c S2 125.0
How can I spread sample_idso that in the end I get this:
我怎样才能传播，sample_id以便最终我得到这个：
gene_symbol S1 S2
a 100 1.3
b 100 14.0
c 112 125.0
回答by jezrael
#df = df[['gene_symbol', 'sample_id', 'fc']]
df = df.pivot(index='gene_symbol',columns='sample_id',values='fc')
print (df)
sample_id S1 S2
gene_symbol
a 100.0 1.3
b 100.0 14.0
c 112.0 125.0
df = df.set_index(['gene_symbol','sample_id'])['fc'].unstack(fill_value=0)
print (df)
sample_id S1 S2
gene_symbol
a 100.0 1.3
b 100.0 14.0
c 112.0 125.0
But if duplicates, need pivot_tableor aggregate with groupbyor , meancan be changed to sum, median, ...:
但如果重复，需要pivot_table或聚合groupby或 ，mean可以更改为sum, median, ...：
df = pd.DataFrame({
'fc': [100,100,112,1.3,14,125, 100],
'sample_id': ['S1','S1','S1','S2','S2','S2', 'S2'],
'gene_symbol': ['a', 'b', 'c', 'a', 'b', 'c', 'c'],
})
print (df)
fc gene_symbol sample_id
0 100.0 a S1
1 100.0 b S1
2 112.0 c S1
3 1.3 a S2
4 14.0 b S2
5 125.0 c S2 <- same c, S2, different fc
6 100.0 c S2 <- same c, S2, different fc
df = df.pivot(index='gene_symbol',columns='sample_id',values='fc')
ValueError: Index contains duplicate entries, cannot reshape
ValueError：索引包含重复条目，无法重塑
df = df.pivot_table(index='gene_symbol',columns='sample_id',values='fc', aggfunc='mean')
print (df)
sample_id S1 S2
gene_symbol
a 100.0 1.3
b 100.0 14.0
c 112.0 112.5
df = df.groupby(['gene_symbol','sample_id'])['fc'].mean().unstack(fill_value=0)
print (df)
sample_id S1 S2
gene_symbol
a 100.0 1.3
b 100.0 14.0
c 112.0 112.5
EDIT:
编辑：
For cleaning set columns nameto Noneand reset_index:
清洁设置columns name为None和reset_index：
df.columns.name = None
df = df.reset_index()
print (df)
gene_symbol S1 S2
0 a 100.0 1.3
1 b 100.0 14.0
2 c 112.0 112.5
回答by MaxU
you can also use pd.crosstab()method:
您还可以使用pd.crosstab()方法：
In [82]: pd.crosstab(index=df.gene_symbol, columns=df.sample_id,
values=df.fc, aggfunc='mean') \
...: .rename_axis(None,1) \
...: .reset_index()
...:
Out[82]:
gene_symbol S1 S2
0 a 100.0 1.3
1 b 100.0 14.0
2 c 112.0 125.0
