We Are Going To Discuss About **pandas get column average/mean**. So lets Start this Python Article.

## pandas get column average/mean

**How to solve pandas get column average/mean**

If you only want the mean of the `weight`

column, select the column (which is a Series) and call `.mean()`

:`In [479]: df Out[479]: ID birthyear weight 0 619040 1962 0.123123 1 600161 1963 0.981742 2 25602033 1963 1.312312 3 624870 1987 0.942120 In [480]: df["weight"].mean() Out[480]: 0.83982437500000007`

**pandas get column average/mean**

If you only want the mean of the `weight`

column, select the column (which is a Series) and call `.mean()`

:`In [479]: df Out[479]: ID birthyear weight 0 619040 1962 0.123123 1 600161 1963 0.981742 2 25602033 1963 1.312312 3 624870 1987 0.942120 In [480]: df["weight"].mean() Out[480]: 0.83982437500000007`

## Solution 1

If you only want the mean of the `weight`

column, select the column (which is a Series) and call `.mean()`

:

```
In [479]: df
Out[479]:
ID birthyear weight
0 619040 1962 0.123123
1 600161 1963 0.981742
2 25602033 1963 1.312312
3 624870 1987 0.942120
In [480]: df["weight"].mean()
Out[480]: 0.83982437500000007
```

Original Author DSM Of This Content

## Solution 2

Try `df.mean(axis=0)`

, `axis=0`

argument calculates the column wise mean of the dataframe so the result will be `axis=1`

is row wise mean so you are getting multiple values.

Original Author Chandu Of This Content

## Solution 3

Do try to give `print (df.describe())`

a shot. I hope it will be very helpful to get an overall description of your dataframe.

Original Author nainometer Of This Content

## Solution 4

Mean for each column in `df`

:

```
A B C
0 5 3 8
1 5 3 9
2 8 4 9
df.mean()
A 6.000000
B 3.333333
C 8.666667
dtype: float64
```

and if you want average of all columns:

```
df.stack().mean()
6.0
```

Original Author Hrvoje Of This Content

## Conclusion

So This is all About **This Tutorial.** Hope This Tutorial Helped You. Thank You.