Add a select accessor to pandas
Project description
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
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file pandas_selectable-1.2.0.tar.gz.
File metadata
- Download URL: pandas_selectable-1.2.0.tar.gz
- Upload date:
- Size: 5.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
441dcaa7d5b813416b11d3698e6008e0352ec955268549c1476cdb45e86809ee
|
|
| MD5 |
08686a408e7153afc95d10820d0ff4f5
|
|
| BLAKE2b-256 |
6179c2ee42b7b1d5ab96eca3ef8abf8cf4bd1a6e5ac977cc66fbaefe9be7bb31
|
File details
Details for the file pandas_selectable-1.2.0-py3-none-any.whl.
File metadata
- Download URL: pandas_selectable-1.2.0-py3-none-any.whl
- Upload date:
- Size: 5.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.11.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9bb1d86883ffd445ce1e3052a0732c8eeea037d84e94f49830ff0ca02979102a
|
|
| MD5 |
71c16c92679be90e99a7b8887e812244
|
|
| BLAKE2b-256 |
fa3a2f57c8f16c368ee1ad51335690662868f303e6a769ef91b00df907c89819
|