# Mean Function in Python pandas (Dataframe, Row and column wise mean)

mean() – Mean Function in python pandas is used to calculate the arithmetic mean of a given set of numbers, mean of a data frame ,column wise mean or mean of column in pandas and row wise mean or mean of rows in pandas , lets see an example of each . We need to use the package name “statistics” in calculation of mean. In this tutorial we will learn,

• How to find the mean of a given set of numbers
• How to find mean of a dataframe in pandas python
• How to find the mean of a column in dataframe in pandas python
• How to find row mean of a dataframe in pandas python

#### Syntax of Mean Function in python pandas

DataFrame.mean(axis=None, skipna=None, level=None, numeric_only=None)

Parameters :

axis : {rows (0), columns (1)}

skipna : Exclude NA/null values when computing the result

level : If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Series

numeric_only : Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series.

#### Simple mean function is shown below

```# calculate arithmetic mean
Import statistics

print(statistics.mean([1,9,5,6,6,7]))
print(statistics.mean([4,-11,-5,16,5,7]))

```

5.66666666667
2.66666666667

#### Mean of a dataframe in pandas python:

Create dataframe

```import pandas as pd
import numpy as np

#Create a DataFrame
d = {
'Rahul','David','Andrew','Ajay','Teresa'],
'Score1':[62,47,55,74,31,77,85,63,42,32,71,57],
'Score2':[89,87,67,55,47,72,76,79,44,92,99,69]}

df = pd.DataFrame(d)
df

```

So the resultant dataframe will be #### Mean of the dataframe in pandas:

```# mean of the dataframe
df.mean()

```

it will calculate the mean of the dataframe across columns so the output will be

Score1  58.0
Score2  73.0
dtype:  float64

Column Mean of the dataframe in pandas python:

```# column mean of the dataframe
df.mean(axis=0)

```

axis=0 argument calculates the column wise mean of the dataframe so the result will be

Score1 58.0
Score2 73.0
dtype: float64

#### Row Mean of the dataframe in pandas python:

```# Row mean of the dataframe
df.mean(axis=1)

```

axis=1 argument calculates the row wise mean of the dataframe so the result will be #### Calculate the mean of the specific Column in pandas

```# mean of the specific column
df.loc[:,"Score1"].mean()

```

the above code calculates the mean of the “Score1” column so the result will be

58.0