如何在Pandas数据框中传播列

Question

我有以下熊猫数据框：

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

产生此结果：

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

我如何传播，sample_id以便最终得到这个：

gene_symbol    S1   S2
a             100   1.3
b             100   14.0
c             112   125.0

Answer 1

使用pivot或unstack：

#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

但是，如果重复，需要pivot_table或集合体groupby，或mean可以改变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：索引包含重复的条目，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

编辑：

对于设置columns name为None和的清洁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