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

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

If you are working with a Series object, you can also use **idxmax()** function.

`series.idxmax()`

Finding the index of the maximum value of numbers in a column in a DataFrame using pandas is easy. We can use the pandas **idxmax()** function to find the index of the maximum value in a column of numbers.

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 maximum value using pandas in the column “Weight”, we can use the pandas **max()** function in the following Python code:

```
print(df["Weight"].max())
# Output:
209.45
```

From looking at the DataFrame above, we can see that the maximum value has index 2. We confirm that by using the **idxmax** function below:

```
print(df["Weight"].idxmax())
# Output:
2
```

If you are looking to find the index of the minimum value of a set of numbers, you can use the pandas **idxmin()** function.

Hopefully this article has been helpful for you to understand how to find the index of maximum value of numbers in a Series or DataFrame using **idxmax()** in pandas.

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