# How to remove rows with null values from kth column onward?

Learn, how to remove rows with null values from kth column onward in Python? By Pranit Sharma Last updated : October 06, 2023

Pandas is a special tool that allows us to perform complex manipulations of data effectively and efficiently. Inside pandas, we mostly deal with a dataset in the form of DataFrame. DataFrames are 2-dimensional data structures in pandas. DataFrames consist of rows, columns, and data.

## Problem statement

Suppose we are given the dataframe with some columns and we need to remove all rows in which elements from column 2 onwards are all NaN.

While creating a DataFrame or importing a CSV file, there could be some NaN values in the cells. NaN values mean “Not a Number” which generally means that there are some missing values in the cell.

## Removing rows with null values from kth column onward

For this purpose, we will simply use the dropna() method where we will use the argument subset and we will assign a list of all those columns from which we want to drop Nan values.

Let us understand with the help of an example,

## Python program to remove rows with null values from kth column onward

```# Importing pandas
import pandas as pd

# Import numpy
import numpy as np

# Creating a dataframe
df = pd.DataFrame({
'one':[1,2,3,4,5],
'two':[1,np.nan,3,4,5],
'three':[1,2,3,4,5],
'four':[1,2,3,4,5],
'five':[1,2,3,4,5]},index=['a','c','e','g','h'])

# Display original DataFrame
print("Original DataFrame:\n",df,"\n")

# Dropping nan values from column 3rd
df.dropna(subset=['two','three','four','five'],how='all',inplace=True)

# Display new df
print("New DataFrame:\n",df,"\n")
```

### Output

The output of the above program is: