pandas: expand data frame column into multiple rows

expand_column.py

"""
Turn this

days      name
[1,3,5,7] John

into this

days    name
1       John
3       John
5       John
7       John

Like spark DataFrame's explode() method

Reference: https://stackoverflow.com/questions/38203352/expand-pandas-dataframe-column-into-multiple-rows
"""

import numpy as np
import pandas as pd

df = pd.DataFrame( {"name": ["John", "Eric"], "days": [[1,3,5,7], [2,4]] } )

# Using numpy's repeat to expand

lens = [ len(item) for item in  df["days"]]
expanded = pd.DataFrame( {"name": np.repeat(df["name"].values, lens), "days": np.concatenate(df["days"].values)} )

# Turn this into a method

def expand(df, expand_column):
  """
  Expand df on expand_column
  df: pandas.DataFrame
  expand_column: the column name to expand
  """
  lens = [ len(item) for item in  df[expand_column]]
  d = {}
  d[expand_column] = np.concatenate(df[expand_column].values)
  
  for col in df.columns.values:
    if col != expand_column:
      d[col] = np.repeat(df[col].values, lens)
  return pd.DataFrame(d)

# TODO
"""
How to turn this

days    result    count
1       true      28
1       false     3
2       true      37
2       false     5

into this

days    true    false
1       28      3
2       37      5

?
"""

To solve the TODO

Using DataFrame.pivot:

df = pd.DataFrame({'days': [1,1,2,2], 'result':['true','false','true','false'], 'count':[28,3,37,5]})
df.pivot(index='days', columns='result', values='count')

Using DataFrame.unstack:

df1 = df.set_index(['days','result']).unstack()
df1.columns = ['false', 'true'] # Optional, change multi-level index to one level