CODEWITHSUNDEEP
pythonpandasplotgroup-byunique
slowmotionnovember
slowmotionnovember

Reputation: 13

Plot count of unique values in Python

I have a data frame that is similar to the following:

   Time                  Account_ID   Device_ID  Zip_Code

0  2011-02-02 12:02:19   ABC123       A12345     83420
1  2011-02-02 13:35:12   EFG456       B98765     37865
2  2011-02-02 13:54:57   EFG456       B98765     37865
3  2011-02-02 14:45:20   EFG456       C24568     37865
4  2011-02-02 15:08:58   ABC123       A12345     83420
5  2011-02-02 15:25:17   HIJ789       G97352     97452

How do I make a plot with the count of unique of account id's on the y-axis and the number of unique device id's associated with a single account id on the x-axis?

So in this instance the "1" bin on the x-axis would have a height of 2 since accounts "ABC123" and "HIJ789" only have 1 unique device id each and the "2" bin would have a height of 1 since account "EFG456" has two unique device id's associated with it.

EDIT

This is the output I got from trying

df.groupby("Account_ID")["Device_ID"].nunique().value_counts().plot.bar()

enter image description here

Upvotes: 1

Views: 267

Answers (1)

bitflip
bitflip

Reputation: 3664

You can combine groupby nunique and value_counts like this:

df.groupby("Account_ID")["Device_ID"].nunique().value_counts().plot.bar()

Edit: Code used to recreate your data:

df = pd.DataFrame({'Time': {0: '2011-02-02 12:02:19', 1: '2011-02-02 13:35:12', 2: '2011-02-02 13:54:57',
                            3: '2011-02-02 14:45:20', 4: '2011-02-02 15:08:58', 5: '2011-02-02 15:25:17'},
                   'Account_ID': {0: 'ABC123', 1: 'EFG456', 2: 'EFG456', 3: 'EFG456', 4: 'ABC123', 5: 'HIJ789'},
                   'Device_ID': {0: 'A12345', 1: 'B98765', 2: 'B98765', 3: 'C24568', 4: 'A12345', 5: 'G97352'},
                   'Zip_Code': {0: 83420, 1: 37865, 2: 37865, 3: 37865, 4: 83420, 5: 97452}})

Upvotes: 1

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