To calculate **percentage change** in pandas, we use the **pct_change()** method. You can calculate percentage change for a series or a dataframe. By default the **pct_change()** method calculates Percentage change between the current and a prior element.

**Formula of Percentage change –**

## Examples –

Let’s read a dataset to work with.

```
import pandas as pd
url = 'https://raw.githubusercontent.com/bprasad26/lwd/master/data/ICICIBANK.NS.csv'
df = pd.read_csv(url)
df.head()
```

### 1 . Calculate Percentage change along the index axis –

By default, the **pct_change()** method calculate the percentage change for a column.

Let’s say we want to calculate the percentage change for the **Open** column.

`df['Open'].pct_change()`

### Periods –

By default, pandas uses the current row and the previous rows for calculating percentage change. But you can change it using the **periods **parameter.

Let’s say you want to calculate percentage change between the current row and 3 rows before that.

`df['Open'].pct_change(periods=3)`

### 2 . Calculate Percentage change along the column axis –

To calculate percentage change for each rows we need to set the axis parameter to **axis=1 or columns**.

Let’s say we want to know the percentage change in opening price and closing price.

`df[['Open','Close']].pct_change(axis=1)`