How to spread a column in a Pandas data frame

Use pivot or 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

But if duplicates, need pivot_table or aggregate with groupby or , mean can be changed to 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

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:

For cleaning set columns name to None and 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