How to count the number of IDs where another column equals a specific value using Pandas?

Asked Oct 10 '21 at 09:56

Active Oct 10 '21 at 10:02

Viewed 19 times

Hi could anyone help me out? I'm trying to group the IDs and have a counter for the number of "t" found in a column for each ID.

f1 = df3[df3['listing_id'].value_counts().reset_index().str.contains('t')]
count = f1['available'].value_counts().reset_index()
print(count)
print(f1)

An example output would be:

   ID   Number of t
14250             1 
12351            10
...

Thanks

edited Oct 10 '21 at 10:02

mozway

194,879
13
39
75

asked Oct 10 '21 at 09:56

seongjoon123

Sorry if I worded this incorrectly. Not sure how to word it. – seongjoon123 Oct 10 '21 at 09:58
1

include an example dataframe in your question so that people don't have to make it themselves, makes it more likely that someone will answer your question. – Vinzent Oct 10 '21 at 09:58
2

try `df.groupby('listing_id')['available'].count()` – Vinzent Oct 10 '21 at 10:00
Will do thanks for the feedback. Did my wording make sense? – seongjoon123 Oct 10 '21 at 10:07

How to count the number of IDs where another column equals a specific value using Pandas?

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