How to count the element in a column and take the result as a new column?

Question

The DataFrame named df is shown as follows.

import pandas as pd 
df = pd.DataFrame({'id': [1, 1, 3]})

Input:

   id
0   1
1   1
2   3

I want to count the number of each id, and take the result as a new column count.

Expected:

    id  count
0   1       2
1   1       2
2   3       1

Answer 1

pd.factorize and np.bincount

My favorite. factorize does not sort and has time complexity of O(n). For big data sets, factorize should be preferred over np.unique

i, u = df.id.factorize()
df.assign(Count=np.bincount(i)[i])

   id  Count
0   1      2
1   1      2
2   3      1

---

np.unique and np.bincount

u, i = np.unique(df.id, return_inverse=True)
df.assign(Count=np.bincount(i)[i])

   id  Count
0   1      2
1   1      2
2   3      1

Answer 2

Assign the new count column to the dataframe by grouping on id and then transforming that column with value_counts (or size).

>>> f.assign(count=f.groupby('id')['id'].transform('value_counts'))
   id  count
0   1      2
1   1      2
2   3      1