convert series returned by pandas.Series.value_counts to a dictionary

Question

I am trying to use pandas.Series.value_counts to get the frequency of values in a dataframe, so I go through each column and get values_count , which gives me a series:

I am struggling to convert this resultant series to a dict:

 groupedData = newData.groupby('class') for k, group in groupedData:     dictClass[k] = {}     for eachlabel in dataLabels:         myobj = group[eachlabel].value_counts()         for eachone in myobj:             print type(myobj)             print myobj 

what I need is a dict :

{'high': 3909 , 'average': 3688, 'less': '182 , 'veryless' : 62} 

Answer 1

If you want to convert a Series to a dict, you could call dict or .to_dict():

>>> s high        3909 average     3688 less         182 veryless      62 dtype: int64 >>> type(s) <class 'pandas.core.series.Series'> >>> dict(s) {'high': 3909, 'average': 3688, 'veryless': 62, 'less': 182} >>> s.to_dict() {'high': 3909, 'average': 3688, 'veryless': 62, 'less': 182} 

Answer 2

Extract keys and values for the dictionary from your_column and then zip it together.

values = df['your_column'].value_counts(dropna=False).keys().tolist() counts = df['your_column'].value_counts(dropna=False).tolist() value_dict = dict(zip(values, counts))