# Max & Min in Python (5 Examples)

This tutorial shows how to **find the maximum and minimum in a list and the columns of a pandas DataFrame** in Python.

Table of contents:

Let’s start right away.

## Example 1: Maximum & Minimum of List Object

The following syntax illustrates how to calculate the maximum and minimum of a list object.

For this example, we first have to create an example list:

my_list = [1, 4, 2, 9, 7, 2, 1, 8, 3, 3, 2, 1] # Create example list print(my_list) # Print example list # [1, 4, 2, 9, 7, 2, 1, 8, 3, 3, 2, 1] |

my_list = [1, 4, 2, 9, 7, 2, 1, 8, 3, 3, 2, 1] # Create example list print(my_list) # Print example list # [1, 4, 2, 9, 7, 2, 1, 8, 3, 3, 2, 1]

In the next step, we can apply the max function to return the maximum of our list:

print(max(my_list)) # Get max of list # 9 |

print(max(my_list)) # Get max of list # 9

As you can see, the max value in our list is 9.

Similar to that, we can apply the min function to return the minimum value in our list:

print(min(my_list)) # Get min of list # 1 |

print(min(my_list)) # Get min of list # 1

The minimum value in our list is 1.

## Example 2: Maximum & Minimum of One Particular Column in pandas DataFrame

In Example 2, I’ll demonstrate how to get the max and min numbers in a pandas DataFrame column.

As a first step, we have to load the pandas library to Python:

import pandas as pd # Import pandas library to Python |

import pandas as pd # Import pandas library to Python

Furthermore, we have to create an example pandas DataFrame:

data = pd.DataFrame({'x1':[5, 2, 4, 2, 2, 3, 9, 1, 7, 5], # Create pandas DataFrame 'x2':range(10, 20), 'group':['A', 'A', 'B', 'B', 'C', 'A', 'C', 'C', 'A', 'B']}) print(data) # Print pandas DataFrame |

data = pd.DataFrame({'x1':[5, 2, 4, 2, 2, 3, 9, 1, 7, 5], # Create pandas DataFrame 'x2':range(10, 20), 'group':['A', 'A', 'B', 'B', 'C', 'A', 'C', 'C', 'A', 'B']}) print(data) # Print pandas DataFrame

As shown in Table 1, the previous Python programming code has created a new pandas DataFrame containing three columns.

Let’s return the maximum value of the variable x1…

print(data['x1'].max()) # Get max of one column # 9 |

print(data['x1'].max()) # Get max of one column # 9

…and the minimum value as well:

print(data['x1'].min()) # Get min of one column # 1 |

print(data['x1'].min()) # Get min of one column # 1

## Example 3: Maximum & Minimum of All Columns in pandas DataFrame

In the previous example, I have explained how to compute the maximum and minimum value in one single column of a pandas DataFrame.

In this example, I’ll explain how to find the maxima and minima of all columns.

For this task, we can apply the max…

print(data.max()) # Get max of all columns # x1 9 # x2 19 # group C # dtype: object |

print(data.max()) # Get max of all columns # x1 9 # x2 19 # group C # dtype: object

…and min functions to our entire data set:

print(data.min()) # Get min of all columns # x1 1 # x2 10 # group A # dtype: object |

print(data.min()) # Get min of all columns # x1 1 # x2 10 # group A # dtype: object

The previous console outputs show the maxima and minima of our three DataFrame columns. Note that even the alphabetical maxima and minima was returned for the group column.

## Example 4: Maximum & Minimum of Rows in pandas DataFrame

The following code demonstrates how to find the max and min values for each row of a pandas DataFrame.

To achieve this, we have to specify the axis argument to be equal to 1 within the max…

print(data.max(axis = 1, numeric_only = True)) # Get max of rows # 0 10 # 1 11 # 2 12 # 3 13 # 4 14 # 5 15 # 6 16 # 7 17 # 8 18 # 9 19 # dtype: int64 |

print(data.max(axis = 1, numeric_only = True)) # Get max of rows # 0 10 # 1 11 # 2 12 # 3 13 # 4 14 # 5 15 # 6 16 # 7 17 # 8 18 # 9 19 # dtype: int64

…and min commands:

print(data.min(axis = 1, numeric_only = True)) # Get min of rows # 0 5 # 1 2 # 2 4 # 3 2 # 4 2 # 5 3 # 6 9 # 7 1 # 8 7 # 9 5 # dtype: int64 |

print(data.min(axis = 1, numeric_only = True)) # Get min of rows # 0 5 # 1 2 # 2 4 # 3 2 # 4 2 # 5 3 # 6 9 # 7 1 # 8 7 # 9 5 # dtype: int64

## Example 5: Maximum & Minimum by Group in pandas DataFrame

It is also possible to get the maxima and minima in the columns of a pandas DataFrame by group.

Example 5 shows how to use the group column in our exemplifying data set to return multiple max and min values.

The following code prints the maxima for each group…

print(data.groupby('group').max()) # Get max by group # x1 x2 # group # A 7 18 # B 5 19 # C 9 17 |

print(data.groupby('group').max()) # Get max by group # x1 x2 # group # A 7 18 # B 5 19 # C 9 17

…and the following Python syntax shows the minima by group:

print(data.groupby('group').min()) # Get min by group # x1 x2 # group # A 2 10 # B 2 12 # C 1 14 |

print(data.groupby('group').min()) # Get min by group # x1 x2 # group # A 2 10 # B 2 12 # C 1 14

## Video & Further Resources

Some time ago, I have published a video on my YouTube channel, which explains the Python codes of this tutorial. You can find the video below:

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Furthermore, you may want to read some related articles on this homepage:

- Max & Min by Group in Python
- Get Max & Min Value of Column & Index in pandas DataFrame
- Max & Min of NumPy Array in Python
- Summary Statistics of pandas DataFrame
- Basic Course for the pandas Library in Python
- Python Programming Examples

In this article, I have shown how to **calculate the maximum and minimum** in the Python programming language. In case you have further questions, please let me know in the comments section.