To find the minimum value of a column in pandas, the easiest way is to use the pandas **min()** function.

`df["Column"].min()`

You can also use the numpy **min()** function.

`np.min(df["Column"])`

Finding the minimum value of numbers in a column, or the minimum value of all numbers in a DataFrame using pandas is easy. We can use the pandas **min()** function to find the minimum values in a column of numbers, or a DataFrame.

Let’s say we have the following DataFrame.

```
df = pd.DataFrame({'Name': ['Jim', 'Sally', 'Bob', 'Sue', 'Jill', 'Larry'],
'Weight': [160.20, 123.81, 209.45, 150.35, 102.43, 187.52]})
print(df)
# Output:
Name Weight
0 Jim 160.20
1 Sally 123.81
2 Bob 209.45
3 Sue 150.35
4 Jill 102.43
5 Larry 187.52
```

To get the minimum value of the numbers in the column “Weight”, we can use the pandas **min()** function in the following Python code:

```
print(df["Weight"].min())
# Output:
102.43
```

Please note, you can use the pandas **min()** function on an entire DataFrame if the DataFrame only contains numbers. If we call it on the DataFrame from above, we will receive an error because the “Name” column is made up of strings.

## Using numpy min to Calculate Minimum Value in pandas DataFrame

We can also use the numpy **min()** function to calculate the minimum value of the numbers in a column in a pandas DataFrame.

To get the minimum value of the numbers in the column “Weight”, we can use the numpy **min()** function in the following Python code:

```
print(np.min(df["Weight"]))
# Output:
102.43
```

As you can see above, this is the same value we received from the pandas **min()** function.

If you are looking to find the minimum value of a set of numbers in regular Python, you can use the python min() function.

If on the other hand you are looking to find the maximum value of a set of numbers, you can use the pandas **max()** function.

Hopefully this article has been helpful for you to understand how to find the minimum value of numbers in a Series or DataFrame in pandas.

## Leave a Reply