Small overview of PyViz capability of data exploration¶
This notebook is intended to present a small overview of PyViz and the capability for data exploration, with interactive plots (show difference between matplotlib and bokeh). Many parts are based on or copied from the official PyViz Tutorial (highly recommended for a more extensive overview of the possibilities of PyViz).
Exploring Pandas Dataframes¶
If your data is in a Pandas dataframe, it’s natural to explore it using the .plot() method (based on Matplotlib). Let’s have a look at some automatic weather station data from Langenferner:
import pandas as pd
url = 'https://cluster.klima.uni-bremen.de/~oggm/tutorials/aws_data_Langenferner_UTC+2.csv'
df = pd.read_csv(url, index_col=0, parse_dates=True)
df.head()
| TEMP | RH | SWIN | SWOUT | LWIN | LWOUT | WINDSPEED | WINDDIR | PRESSURE | |
|---|---|---|---|---|---|---|---|---|---|
| 2013-07-13 00:00:00 | 1.634333 | 67.595753 | 0.0 | 0.0 | 212.744817 | 303.656833 | 4.436833 | 211.533333 | 692.622250 |
| 2013-07-13 01:00:00 | 1.388667 | 68.150512 | 0.0 | 0.0 | 209.781683 | 302.588717 | 5.544000 | 206.166667 | 692.395683 |
| 2013-07-13 02:00:00 | 1.064500 | 66.853977 | 0.0 | 0.0 | 207.234933 | 300.872133 | 5.573167 | 210.750000 | 692.200800 |
| 2013-07-13 03:00:00 | 0.985167 | 55.827547 | 0.0 | 0.0 | 207.913533 | 295.684267 | 3.970167 | 203.250000 | 692.163967 |
| 2013-07-13 04:00:00 | 1.155333 | 43.371014 | 0.0 | 0.0 | 211.513517 | 292.688400 | 3.267000 | 203.366667 | 692.001667 |
Just calling .plot() won’t give anything meaningful, because of the different magnitudes of the parameters:
df.plot();
Of course we can have a look at one variable only:
df.TEMP.plot();
This creates a static plot using matplotlib. With this approach we also can make some further explorations, like calculating the monthly mean temperature:
dfm = df.resample('m').mean()
dfm.TEMP.plot();
We can see the course of the parameter but we can not tell what was the exact temperature at January and we also cannot zoom in.