# What does axis in pandas mean?

Here is my code to generate a dataframe:

```
import pandas as pd
import numpy as np
dff = pd.DataFrame(np.random.randn(1,2),columns=list('AB'))
```

then I got the dataframe:

```
+------------+---------+--------+
| | A | B |
+------------+---------+---------
| 0 | 0.626386| 1.52325|
+------------+---------+--------+
```

When I type the commmand :

```
dff.mean(axis=1)
```

I got :

```
0 1.074821
dtype: float64
```

According to the reference of pandas, axis=1 stands for columns and I expect the result of the command to be

```
A 0.626386
B 1.523255
dtype: float64
```

So here is my question: what does axis in pandas mean?

It specifies the axis **along which** the means are computed. By default `axis=0`

. This is consistent with the `numpy.mean`

usage when `axis`

is specified *explicitly* (in `numpy.mean`

, axis==None by default, which computes the mean value over the flattened array) , in which `axis=0`

along the *rows* (namely, *index* in pandas), and `axis=1`

along the *columns*. For added clarity, one may choose to specify `axis='index'`

(instead of `axis=0`

) or `axis='columns'`

(instead of `axis=1`

).

```
+------------+---------+--------+
| | A | B |
+------------+---------+---------
| 0 | 0.626386| 1.52325|----axis=1----->
+------------+---------+--------+
| |
| axis=0 |
↓ ↓
```

From: stackoverflow.com/q/22149584