GitLocker: The Coding Marketplace

Description:

pandasselectable 1.2.0

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.is_month_start
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