pandas-selectable

What Is It?

pandas-selectable adds a select accessor to pandas DataFrames and Series. It's like query but with the niceties of tab-completion.

Quickstart

In [1]: import numpy as np
In [2]: import pandas as pd
In [3]: import pandas_selectable  # magic
In [4]: dta = pd.DataFrame.from_dict({    ...:     'X': ['A', 'B', 'C'] * 5,    ...:     'Y': np.arange(1, 16),    ...:     'Z': pd.date_range('2020-01-01', periods=15)    ...: })
In [5]: dta.head() Out[5]:    X  Y          Z 0  A  1 2020-01-01 1  B  2 2020-01-02 2  C  3 2020-01-03 3  A  4 2020-01-04 4  B  5 2020-01-05
In [6]: dta.select.X == 'B' Out[6]:     X   Y          Z 1   B   2 2020-01-02 4   B   5 2020-01-05 7   B   8 2020-01-08 10  B  11 2020-01-11 13  B  14 2020-01-14
In [7]: dta.select.Z >= '2020-01-03' Out[7]:     X   Y          Z 2   C   3 2020-01-03 3   A   4 2020-01-04 4   B   5 2020-01-05 5   C   6 2020-01-06 6   A   7 2020-01-07 7   B   8 2020-01-08 8   C   9 2020-01-09 9   A  10 2020-01-10 10  B  11 2020-01-11 11  C  12 2020-01-12 12  A  13 2020-01-13 13  B  14 2020-01-14 14  C  15 2020-01-15
In [8]: dta.select.X.str.contains('A') Out[8]:     X   Y          Z 0   A   1 2020-01-01 3   A   4 2020-01-04 6   A   7 2020-01-07 9   A  10 2020-01-10 12  A  13 2020-01-13
In [9]: dta.select.Z.dt.ismonthstart Out[9]:    X  Y          Z 0  A  1 2020-01-01

It also works for Series.

In [10]: dta.X.select == 'A'
Out[10]:
0     A
3     A
6     A
9     A
12    A
Name: X, dtype: object

Though the string and datetime accessor APIs are slightly inconsistent. They're available via the select accessor now.

In [11]: dta.X.select.str.contains('B')
Out[11]:
1     B
4     B
7     B
10    B
13    B
Name: X, dtype: object

Requirements

pandas >= 1.1

Installation

pip install pandas-selectable