How to get the number of the most frequent value in a column?

python pandas counter frequency series
Roman picture Roman · Feb 28, 2013 · Viewed 82.5k times · Source

I have a data frame and I would like to know how many times a given column has the most frequent value.

I try to do it in the following way:

items_counts = df['item'].value_counts()
max_item = items_counts.max()

As a result I get:

ValueError: cannot convert float NaN to integer

As far as I understand, with the first line I get series in which the values from a column are used as key and frequency of these values are used as values. So, I just need to find the largest value in the series and, because of some reason, it does not work. Does anybody know how this problem can be solved?

Answer

beardc picture beardc · Feb 28, 2013

It looks like you may have some nulls in the column. You can drop them with df = df.dropna(subset=['item']). Then df['item'].value_counts().max() should give you the max counts, and df['item'].value_counts().idxmax() should give you the most frequent value.

Related questions

Transform a Counter object into a Pandas DataFrame

I used Counter on a list to compute this variable: final = Counter(event_container) print final gives: Counter({'fb_view_listing': 76, 'fb_homescreen': 63, 'rt_view_listing': 50, 'rt_home_start_app': 46, 'fb_view_wishlist': 39, 'fb_view_product': 37, 'fb_search': 29, 'rt_view_…

Read More
Count occurences of True/False in column of dataframe

Is there a way to count the number of occurrences of boolean values in a column without having to loop through the DataFrame? Doing something like df[df["boolean_column"]==False]["boolean_column"].sum() Will not work because False has …

Read More
Python: Removing Rows on Count condition

I have a problem filtering a pandas dataframe. city NYC NYC NYC NYC SYD SYD SEL SEL ... df.city.value_counts() I would like to remove rows of cities that has less than 4 count frequency, which would be SYD and …

Read More