Hello Guys, How are you all? Hope You all Are Fine. Today We Are Going To learn about **How do I subtract the previous row from the current row in a pandas dataframe and apply it to every row; without using a loop** **in Python**. So Here I am Explain to you all the possible Methods here.

Without wasting your time, Let’s start This Article.

Table of Contents

## How do I subtract the previous row from the current row in a pandas dataframe and apply it to every row; without using a loop?

**How do I subtract the previous row from the current row in a pandas dataframe and apply it to every row; without using a loop?**MaxU solutions suits in your case. If you want to perform more complex computations based on your previous rows you should use shift

**subtract the previous row from the current row in a pandas dataframe and apply it to every row; without using a loop**MaxU solutions suits in your case. If you want to perform more complex computations based on your previous rows you should use shift

## Method 1

you can use pct_change() or/and diff() methods

Demo:

In [138]: df.Close.pct_change() * 100 Out[138]: 0 NaN 1 0.469484 2 0.467290 3 -0.930233 4 0.469484 5 0.467290 6 0.000000 7 -3.255814 8 -3.365385 9 -0.497512 Name: Close, dtype: float64 In [139]: df.Close.diff() Out[139]: 0 NaN 1 0.125 2 0.125 3 -0.250 4 0.125 5 0.125 6 0.000 7 -0.875 8 -0.875 9 -0.125 Name: Close, dtype: float64

## Method 2

MaxU solutions suits in your case. If you want to perform more complex computations based on your previous rows you should use shift

**Conclusion**

It’s all About this issue. Hope all Methods helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which Method worked for you? Thank You.

**Also, Read**