# 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.
Submitted by Pranit Sharma, on November 09, 2022

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.

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

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

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 code 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:

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