# How to do statistics on a DataFrame

• 0 minPandas library provides a wide range of statistical methods that can be applied to a DataFrame.

## Here are some common statistics you can perform on a DataFrame:

- mean
- median
- mode
- std
- var
- min, max
- sum
- count
- describe

### Mean

```
df.mean()
```

### Median

```
df.median()
```

### Mode

```
df.mode()
```

### Standard Deviation

```
df.std()
```

### Variance

```
df.var()
```

### Minimum or Maximum

```
df.min()
df.max()
```

### Sum

```
df.sum()
```

### Count

```
df.count()
```

### All at a time

```
df.describe()
```

You can also use more advanced statistical methods such as correlation, covariance, etc. using the `.corr()`

, `.cov()`

etc.

Note that these are just a few examples of the statistical methods available in Pandas. The library offers many more methods for performing more complex statistics on DataFrames.