How to Count Number of Rows or Columns in a Pandas DataFrame

Published Sep 7, 2022  ∙  Updated Sep 8, 2022

Let’s see how we can count the number of rows and columns in a Pandas DataFrame.

We’ll also include how to count non-null rows.

1. Count number of rows in a DataFrame

1.1. Number of rows

Any of the three options below are available to obtain the total number of rows (null or non-null).

len(df.index)
len(df)
df.shape[0]

1.2. Number of non-null rows

We can obtain non-null row count, which ignore NaN values.

df.count()

We can also get the number of non-null values in first column.

df[df.columns[0]].count()

count() returns a DataFrame of non-null counts for each column (i.e. non-null counts vary by column).

1.3. Number of rows per group

df.groupby(...).size()

size() returns a Series (i.e. all columns in a group share the same row count).

1.4. Number of non-null rows per group

df.groupby(...).count()

Let’s obtain a non-null count for a specific column in one group.

df.groupby(...)['colName'].count()

When count() is called on a specific column, it will return a Series.

2. Count number of columns in a DataFrame

df.shape[1]
len(df.columns)