**Summary : **in this tutorial, you’ll learn about the axes and labels in Pandas.

## Pandas Axes

NumPy can be used to perform calculations on multi-dimensional arrays and matrices. Our data is normally available in tabular form, which can be represent in 2-dimensional array, equivalent to 2 axis.

The term **axes **in Pandas refer to **the columns and the row index**, as shown in the picture above.

The index is axis 0 and the columns are axis 1. Both are stored in `Index`

objects and are immutable, meaning they cannot be changed once created.

## Pandas Labels

The labels in pandas allows for quick and easy access to rows and columns data using names instead of numbers.

```
# Subset a single column by column name
df["colB"]
df.colA
# Accessing a single element in a DataFrame
df["colB"]["R3"], df["colB"][1]
```

Code language: Python (python)

More details on how to select data using labels can be found at Select DataFrame rows and Select DataFrame columns.