Pandas DataFrame ‘count()’ Method
Table Of Contents:
- Syntax Of ‘count( )’ Method In Pandas.
- Examples ‘count( )’ Method.
(1) Syntax:
DataFrame.count(axis=0, level=None, numeric_only=False)Description:
- Count non-NA cells for each column or row.
- The values None, NaN, NaT, and optionally numpy.inf (depending on pandas.options.mode.use_inf_as_na) are considered NA.
Parameters:
- axis{0 or ‘index’, 1 or ‘columns’}, default 0 :
- If 0 or ‘index’ counts are generated for each column. If 1 or ‘columns’ counts are generated for each row.
- level: int or str, optional –
- If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a DataFrame. A str specifies the level name.
- numeric_only: bool, default False –
- Include only float, int or boolean data
Returns:
- Series or DataFrame – For each column/row the number of non-NA/null entries. If level is specified returns a DataFrame.
(2) Examples Of count() Method:
Example-1
df = pd.DataFrame({"Person":
["John", "Myla", "Lewis", "John", "Myla"],
"Age": [24., np.nan, 21., 33, 26],
"Single": [False, True, True, True, False]})
dfOutput:
# Counting Each Column Value
df.count()Output:
Person 5
Age 4
Single 5
dtype: int64Note:
- Notice the uncounted NA values.
# Counting Each Row Value
df.count(axis='columns')Output:
0 3
1 2
2 3
3 3
4 3
dtype: int64