Convenience functions for grouping datetimes in pandas
Project description
# groupby
Convenience functions for grouping datetimes in [pandas](http://www.github.com/pydata/pandas).
## Requirements
* [numpy](http://www.github.com/numpy/numpy)
* [pandas](http://www.github.com/pydata/pandas)
## Examples
```python
import groupbytime
import matplotlib.pyplot as plt
grouped = groupbytime.groupby_times(df, 'weekly')
weekly_mean = grouped.mean()
# plotting timedeltas doesn't really work in pandas so this helps
import matplotlib.pyplot as plt
grouped.plot_timedelta(weekly_mean)
```
Convenience functions for grouping datetimes in [pandas](http://www.github.com/pydata/pandas).
## Requirements
* [numpy](http://www.github.com/numpy/numpy)
* [pandas](http://www.github.com/pydata/pandas)
## Examples
```python
import groupbytime
import matplotlib.pyplot as plt
grouped = groupbytime.groupby_times(df, 'weekly')
weekly_mean = grouped.mean()
# plotting timedeltas doesn't really work in pandas so this helps
import matplotlib.pyplot as plt
grouped.plot_timedelta(weekly_mean)
```
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
groupbytime-0.3.2.tar.gz
(3.6 kB
view hashes)
Built Distribution
Close
Hashes for groupbytime-0.3.2-py2.py3-none-any.whl
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 815afd3fb930026fb576ac5842832b21efb1ec6c0dd4c67313544f9ba20fec68 |
|
| MD5 | b4516f7cafe72ba52cc51068c10114b8 |
|
| BLAKE2b-256 | 4ac6adc669428e276c3a51ce29cabfcb9c9a2c748c86a5db6f27a3528b812079 |
