pandas_summary

An extension to pandas dataframes describe function.

The module contains `DataFrameSummary`

object that extend `describe()`

with:

**properties**- dfs.columns_stats: counts, uniques, missing, missing_perc, and type per column
- dsf.columns_types: a count of the types of columns
- dfs[column]: more in depth summary of the column

**function**- summary(): extends the
`describe()`

function with the values with`columns_stats`

- summary(): extends the

Installation

The module can be easily installed with pip:

```
> pip install pandas-summary
```

This module depends on `numpy`

and `pandas`

. Optionally you can get also some nice visualisations if you have `matplotlib`

installed.

Tests

To run the tests, execute the command `python setup.py test`

Usage

The module contains one class:

DataFrameSummary

The `DataFrameSummary`

expect a pandas `DataFrame`

to summarise.

```
from pandas_summary import DataFrameSummary
dfs = DataFrameSummary(df)
```

getting the columns types

```
dfs.columns_types
numeric 9
bool 3
categorical 2
unique 1
date 1
constant 1
dtype: int64
```

getting the columns stats

```
dfs.columns_stats
A B C D E
counts 5802 5794 5781 5781 4617
uniques 5802 3 5771 128 121
missing 0 8 21 21 1185
missing_perc 0% 0.14% 0.36% 0.36% 20.42%
types unique categorical numeric numeric numeric
```

getting a single column summary, e.g. numerical column

```
# we can also access the column using numbers A[1]
dfs['A']
std 0.2827146
max 1.072792
min 0
variance 0.07992753
mean 0.5548516
5% 0.1603367
25% 0.3199776
50% 0.4968588
75% 0.8274732
95% 1.011255
iqr 0.5074956
kurtosis -1.208469
skewness 0.2679559
sum 3207.597
mad 0.2459508
cv 0.5095319
zeros_num 11
zeros_perc 0,1%
deviating_of_mean 21
deviating_of_mean_perc 0.36%
deviating_of_median 21
deviating_of_median_perc 0.36%
top_correlations {u'D': 0.702240243124, u'E': -0.663}
counts 5781
uniques 5771
missing 21
missing_perc 0.36%
types numeric
Name: A, dtype: object
```

Future development

Summary analysis between columns, i.e. `dfs[[1, 2]]`