Pandas Series of lists to one series

Question

I have a Pandas Series of lists of strings:

0                           [slim, waist, man]
1                                [slim, waistline]
2                       


        

Answer 1

series_name.sum()

does exactly what you need. Do make sure it's a series of lists otherwise your values will be concatenated (if string) or added (if int)

Answer 2

You may also try:

combined = []
for i in s.index:
    combined = combined + s.iloc[i]

print(combined)

s = pd.Series(combined)
print(s)

output:

['slim', 'waist', 'man', 'slim', 'waistline', 'santa']

0         slim
1        waist
2          man
3         slim
4    waistline
5        santa

dtype: object

Answer 3

In pandas version 0.25.0 appeared a new method 'explode' for series and dataframes. Older versions do not have such method.

It helps to build the result you need.

For example you have such series:

import pandas as pd

s = pd.Series([
    ['slim', 'waist', 'man'],
    ['slim', 'waistline'],
    ['santa']])

Then you can use

s.explode()

To get such result:

0         slim
0        waist
0          man
1         slim
1    waistline
2        santa

In case of dataframe:

df = pd.DataFrame({
  's': pd.Series([
    ['slim', 'waist', 'man'],
    ['slim', 'waistline'],
    ['santa']
   ]),
   'a': 1
})

You will have such DataFrame:

                    s  a
0  [slim, waist, man]  1
1   [slim, waistline]  1
2             [santa]  1

Applying explode on s column:

df.explode('s')

Will give you such result:

           s  a
0       slim  1
0      waist  1
0        man  1
1       slim  1
1  waistline  1
2      santa  1

If your series, contain empty lists

import pandas as pd

s = pd.Series([
    ['slim', 'waist', 'man'],
    ['slim', 'waistline'],
    ['santa'],
    []
])

Then running explode will introduce NaN values for empty lists, like this:

0         slim
0        waist
0          man
1         slim
1    waistline
2        santa
3          NaN

If this is not desired, you can dropna method call:

s.explode().dropna()

To get this result:

0         slim
0        waist
0          man
1         slim
1    waistline
2        santa

Dataframes also have dropna method:

df = pd.DataFrame({
  's': pd.Series([
    ['slim', 'waist', 'man'],
    ['slim', 'waistline'],
    ['santa'],
    []
   ]),
   'a': 1
})

Running explode without dropna:

df.explode('s')

Will result into:

           s  a
0       slim  1
0      waist  1
0        man  1
1       slim  1
1  waistline  1
2      santa  1
3        NaN  1

with dropna:

df.explode('s').dropna(subset=['s'])

Result:

           s  a
0       slim  1
0      waist  1
0        man  1
1       slim  1
1  waistline  1
2      santa  1