Even after converting a dataframe into dictionary, its type remains as a pandas dataframe

Question

I have a dataframe like the one below

--> playstore_df['App'].value_counts()

ROBLOX                 9
8 Ball Pool            7
Bubble Shooter         6
Helix Jump             6
Zombie Catchers        6

On the left we have app names, and on right, its count (i.e. how many times it has occurred in the dataset)

I stored it into a variable called app_count. To convert this into a dictionary, I used the to_dict() function.

--> app_count.to_dict()

The following was the output:

{'ROBLOX': 9,
 '8 Ball Pool': 7,
 'Bubble Shooter': 6,
 'Helix Jump': 6,
 'Zombie Catchers': 6}

But when I check the type of app_count using the following function:

--> type(app_count)

It gives the output as:

pandas.core.series.Series

Answer 1

DataFrame.to_dict() does not operate in-place. It will return a dictionary containing the DataFrame's content (like you saw when using app_count.to_dict()), but the original df will remain unchanged. To save the modifications, you need to store them back to the original variable like so:

app_count = app_count.to_dict()

Now, app_count will be a dictionary.

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Side note: if you don't need the original Series/DataFrame, you can also get the dictionary in one line:

app_count = playstore_df['App'].value_counts().to_dict()