# Return max of zero or value for a pandas DataFrame column

Given a pandas dataframe, we have to get the max of zero or value for its column. By Pranit Sharma Last updated : October 03, 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

Here, we are given a DataFrame with multiple columns and we need to replace the negative values in this pandas DataFrame with zero.

## Returning the max of zero or value for a DataFrame column

We can use the pandas.DataFrame.clip() method of dataframe.

The pandas.DataFrame.clip() is used to trim values at specified input threshold. We can use this function to put a lower limit and upper limit on the values that any cell can have in the dataframe. So we will first create a DataFrame with some positive and negative values and then we will update the column of this DataFrame by using the chain method inside which we will assign 0 as the lower limit value.

Let us understand with the help of an example,

## Python program to get the max of zero or value for a pandas DataFrame column

```# Importing pandas package
import pandas as pd

# Importing numpy package
import numpy as np

# Creating a dictionary
d = {'value': np.arange(-5,5)}

# Creating a DataFrame
df = pd.DataFrame(d)

# Display dataframe
print('Original DataFrame:\n',df,'\n')

# Replacing negative values
df['value'] = df['value'].clip(0, None)

# Display result
print('Result:\n',df,'\n')
```

### Output

The output of the above program is:

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