# Pandas Technique: Summary Statistics

Summary statistics is a part of descriptive statistics that summarizes and provides the gist of information about the sample data. Statisticians commonly try to describe and characterize the observations by finding: a measure of location, or central tendency, such as the arithmetic mean.

**import** pandas **as** pd
**import** numpy **as** np

*# read dataset*
df **=** pd**.**read_csv('Srt_dta.csv')
df

**Summarizing numerical data**

`df['Height(cm)']`**.**mean()

`'2011-12-11'`

`df['Date of Birth']`**.**max()

`'2018-02-27'`

**The .agg() method**

agg() is used to pass a function or list of function to be applied on a series or even each element of series separately. In case of list of function, multiple results are returned by agg() method.

**def** pct30(column):
**return** column**.**quantile(0.3)
df['Weight(kg)']**.**agg(pct30)

`21.0`

**Summaries on multiple columns**

`df[['Height(cm)', 'Weight(kg)']]`**.**agg(pct30)

```
Height(cm) 45.4
Weight(kg) 21.0
dtype: float64
```

**Multiple summaries**

**def** pct40(column):
**return** column**.**quantile(0.4)
df['Height(cm)']**.**agg([pct30, pct40])

```
pct30 45.4
pct40 47.2
Name: Height(cm), dtype: float64
```

**Cumulative sum**

`df['Weight(kg)']`**.**cumsum()
*# another method
# .cummax()
# .cumprod()
# .cummin()*

```
0 25
1 48
2 70
3 87
4 116
5 118
6 192
Name: Weight(kg), dtype: int64
```

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