Putting a dict into a dataframe - python

Question

I have a list called 'gender', of which I counted all the occurrences of the values with Counter:

gender = ['2',
          'Female,',
          'All Female Group,',
          'All Male Group,',
          'Female,',
          'Couple,',
          'Mixed Group,'....]

gender_count = Counter(gender)
gender_count 
Counter({'2': 1,
     'All Female Group,': 222,
     'All Male Group,': 119,
     'Couple,': 256,
     'Female,': 1738,
     'Male,': 2077,
     'Mixed Group,': 212,
     'NA': 16})

I want to put this dict into a pandas Dataframe. I have used pd.series(Convert Python dict into a dataframe):

s = pd.Series(gender_count, name='gender count')
s.index.name = 'gender'
s.reset_index()

Which gives me the dataframe I want, but I don't know how to save these steps into a pandas DataFrame. I also tried using DataFrame.from_dict()

s2 = pd.DataFrame.from_dict(gender_count, orient='index')

But this creates a dataframe with the categories of gender as the index.

I eventually want to use gender categories and the count for a piechart.

just add reset_index at the end of your s2 creation statement — Zeugma
– Zeugma, Commented Mar 29, 2017 at 16:42
That works! Is there a way I can now change the column names? I tried .rename_axis() but that didn't work. — Lisadk
– Lisadk, Commented Mar 29, 2017 at 16:49

piRSquared · Accepted Answer · 2017-03-29 18:00:56Z

3

Skip the intermediate step

gender = ['2',
          'Female',
          'All Female Group',
          'All Male Group',
          'Female',
          'Couple',
          'Mixed Group']

pd.value_counts(gender)

Female              2
2                   1
Couple              1
Mixed Group         1
All Female Group    1
All Male Group      1
dtype: int64

answered Mar 29, 2017 at 18:00

piRSquared

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MaxU - stand with Ukraine · Accepted Answer · 2017-03-29 16:36:45Z

2

In [21]: df = pd.Series(gender_count).rename_axis('gender').reset_index(name='count')

In [22]: df
Out[22]:
              gender  count
0                  2      1
1  All Female Group,    222
2    All Male Group,    119
3            Couple,    256
4            Female,   1738
5              Male,   2077
6       Mixed Group,    212
7                 NA     16

answered Mar 29, 2017 at 16:36

MaxU - stand with Ukraine

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2 Comments

Lisadk Over a year ago

I used your code, but this gives me the error message 'str' object is not callable, for 'gender' and 'count'.

root Over a year ago

@Lisadk: You're likely using an older version of pandas. See the output of pd.__version__.

ℕʘʘḆḽḘ · Accepted Answer · 2017-03-29 16:30:09Z

0

what about just

s = pd.DataFrame(gender_count)

answered Mar 29, 2017 at 16:30

ℕʘʘḆḽḘ

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2 Comments

Lisadk Over a year ago

Since 'gender_count' is a dict, this does not work (ValueError: If using all scalar values, you must pass an index). EDIT: when you put in index=[0], it gives me the categories of gender as the columns.

Lisadk Over a year ago

This gives me the categories of gender as the columns. I would like 'gender' and 'count' as the colums.

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