In this Python Pandas tutorial, we will learn about **Count Rows in Python Pandas Dataframe**. Also, we will cover these topics.

- Count Rows in Pandas DataFrame
- Count Entries in Pandas DataFrame
- Count Duplicate Rows in Pandas DataFrame
- Count Distinct rows in Pandas DataFrame
- Count Unique Rows in Pandas DataFrame
- Count Rows in a Pandas DataFrame that Satisfies a Condition
- Count Records in Pandas df
- Count Rows in Series Pandas

**Table of Contents**show

## Count Rows in Pandas DataFrame

In this section, we will learn how to **count rows in Pandas DataFrame**.

- Using count() method in Python Pandas we can count the rows and columns.
- Count method requires axis information, axis=1 for column and axis=0 for row.
- To count the rows in Python Pandas type
`df.count(axis=1)`

, where df is the dataframe and axis=1 refers to column.

`df.count(axis=1)`

**Implementation on Jupyter Notebook**

Read Python Pandas CSV Tutorial

## Count Entries in Pandas DataFrame

In this section, we will learn how to **count entries in Pandas dataframe in Python**.

- Using count() method in Python Pandas we can count total entries for in each column.
- Count method accepts axis information, axis=1 is for column and axis=0 is for row.
- To count the rows in Python Pandas type
`df.count(axis=1)`

, where df is the dataframe and axis=1 refers to column.

`df.count(axis=0)`

**Implementation on Jupyter Notebook**

Read Python Pandas DataFrame Iterrows

## Count Duplicate Rows in Pandas DataFrame

In this section, we will learn about **count duplicate rows in pandas dataframe**.

- There are multiple ways of counting duplicate rows in Python Pandas but most efficient on is using pivot table.
- Pivot table accepts index or list of columns and aggregate function.

`df.pivot_table(index = ['Brand', 'Model', 'Accel', 'TopSpeed'], aggfunc ='size')`

**Implementation on Jupyter Notebook**

Read Python convert DataFrame to list

## Count Distinct rows in Pandas DataFrame

In this section, we will learn **how to count distinct rows in pandas dataframe**.

- Distinct rows means rows that are not similar to each other or unique rows.
- Using value_count() method we can find out the distict rows in pandas dataframe.
- value_count returns each of distinct value of specified column.
- In our example, we have implemented it on Model column.

`df['Model'].value_counts()`

**Implementation on Jupyter Notebook**

Check out, Pandas Delete Column

## Count Unique Rows in Pandas DataFrame

In this section, we will **count unique rows in Pandas dataframe in Python**.

- Using nunique() method, we can
**count unique rows in pandas**. - by default nunique() shows axis=0 that means rows but it can be changed to axis=1.
- Here is the syntax:

`df.nunique()`

**Implementation on Jupyter Notebook**

Read How to Convert Pandas DataFrame to a Dictionary

## Count Rows in a Pandas DataFrame that Satisfies a Condition

In this section, we will learn **how to count rows in a pandas dataframe that satisfies a condition**.

- There can be any kind of condition to filter out the data so in our case we’ll consider all those columns whose price is above 5000 Euro.
- Here is the code to perform above condition.

`df[df['PriceEuro'] > 50000].count()`

**Implementation on Jupyter Notebook**

Check out, Python Pandas Drop Rows Example

## Count Rows in Series Pandas

In this section, we will learn how to **count rows in series pandas in python**.

- Using
`series.count()`

, we can count the series in Python Pandas. - It is similar as we did with DataFrame. In our example, we have created series and then performed operation on it.

**Implementation on Jupyter Notebook**

**Related Posts:**

- How to use Pandas drop() function in Python
- Groupby in Python Pandas
- Pandas replace multiple values
- Crosstab in Python Pandas
- Python Pandas Write DataFrame to Excel
- Missing Data in Pandas in Python
- Get index Pandas Python

In this tutorial, we have learned about **Count Rows in Python Pandas Dataframe**. Also, we have covered these topics.

- Count Rows in Pandas DataFrame
- Count Entries in Pandas DataFrame
- Count Duplicate Rows in Pandas DataFrame
- Count Distinct rows in Pandas DataFrame
- Count Unique Rows in Pandas DataFrame
- Count Rows in a Pandas DataFrame that Satisfies a Condition
- Count Records in Pandas df
- Count Rows in Series Pandas

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