Convert pandas DataFrame column of comma separated strings to one-hot encoded

Question

I have a large dataframe (‘data’) made up of one column. Each row in the column is made of a string and each string is made up of comma separated categories. I wish to one hot encode this data.

For example,

data = {"mesh": ["A, B, C", "C,B", ""]}

From this I would like to get a dataframe consisting of:

index      A       B.     C
0          1       1      1
1          0       1      1
2          0       0      0

How can I do this?

Answer 1

Note that you're not dealing with OHEs.

str.split + stack + get_dummies + sum

df = pd.DataFrame(data)
df

      mesh
0  A, B, C
1      C,B
2         

(df.mesh.str.split('\s*,\s*', expand=True)
   .stack()
   .str.get_dummies()
   .sum(level=0))
df

   A  B  C
0  1  1  1
1  0  1  1
2  0  0  0

---

apply + value_counts

(df.mesh.str.split(r'\s*,\s*', expand=True)
   .apply(pd.Series.value_counts, 1)
   .iloc[:, 1:]
   .fillna(0, downcast='infer'))

   A  B  C
0  1  1  1
1  0  1  1
2  0  0  0

---

pd.crosstab

x = df.mesh.str.split('\s*,\s*', expand=True).stack()
pd.crosstab(x.index.get_level_values(0), x.values).iloc[:, 1:]
df

col_0  A  B  C
row_0         
0      1  1  1
1      0  1  1
2      0  0  0