I have a data frame like this:
IP_address
IP1
IP1
IP1
IP4
IP4
IP4
IP4
IP4
IP7
IP7
IP7
I would like to take count of unique values in this column and add the count as a variable by itself. At the end, it should look like this:
IP_address IP_address_Count
IP1 3
IP1 3
IP1 3
IP4 5
IP4 5
IP4 5
IP4 5
IP4 5
IP7 3
IP7 3
IP7 3
I am able to take the unique values of the column using the below code:
unique_ip_address_count = (df_c_train.drop_duplicates().IP_address.value_counts()).to_dict()
However, I am not sure how to match these in a loop in python so that i can get the desired results in python. Any sort of help is much appreciated.
I am not able to find a equivalent answer in stackoverflow. If there is anything please direct me there. Thank you.
To count unique values in the pandas dataframe column use Series. unique() function and then call the size to get the count. Series.
read_csv() function in which pass the path and name of the dataset. Select the column in which you want to check or count the unique values. For finding unique values we are using unique() function provided by pandas and stored it in a variable, let named as 'unique_values'.
You can use value_counts() with map
df['count'] = df['IP_address'].map(df['IP_address'].value_counts())
IP_address count
0 IP1 3
1 IP1 3
2 IP1 3
3 IP4 5
4 IP4 5
5 IP4 5
6 IP4 5
7 IP4 5
8 IP7 3
9 IP7 3
10 IP7 3
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