Trusted answers to developer questions
How to take count of non-NA values in a column or row
Overview
The count() function is used to take count of non-NA (None, NaN, NaT values) cells present in a column or row or a DataFrame object.
Syntax
DataFrame.count(axis=0, level=None, numeric_only=False)
Syntax for the count() function in Pandas
Parameters
axis: This takes either0(orindex) or1(orcolumns) for the counts to be generated for either thecolumnsor therows, respectively.level: This takes a string level name to take count along with the given level.numeric_only: This takes a boolean value indicating if only float, integer, or boolean values should be included.
Return value
This function returns a DataFrame showing the number of non-null entries in it.
Example
# A code to illustrate the count() function in Pandas# importing the pandas and numpy librariesimport pandas as pdimport numpy as np# creating a dataframedf = pd.DataFrame({"Person":["John", "Myla", "Lewis", "John", "Myla"],"Age": [24., np.nan, 21., 33, 26],"Single": [False, True, True, True, False]})# printing the dataframe objectprint(df)# taking count of the non-NA values in present in the columnsprint(" This is a dataframe of each columns and their Number of non-NA values: ", df.count())# taking the count of the non-NA values in each of the rowsprint("These are the number of non-NA values in each of the rows: ", df.count(axis=1))
Explanation
- Lines 4–5: We import the necessary libraries.
- Lines 8–11: We create a DataFrame object,
df. - Line 15: We print
df. - Line 18: We take count of the number of non-NA values in the columns of the DataFrame using the
count()function. - Line 21: We take count of the number of non-NA values in the rows of the DataFrame using the
count()function.
RELATED TAGS
pandas
python
CONTRIBUTOR
Onyejiaku Theophilus ChidaluTRENDING TOPICS
Did you find this helpful?