This shows the bare minimum needed to get started with Kaskada.
Install
Install the latest version. This uses kaskada>=0.6.0-a.3 to ensure the pre-release version is installed.
pip install kaskada>=0.6.0-a.3
See the section on installation to learn more about installing Kaskada.
Write a query
The following Python code imports the Kaskada library, creates a session, and loads some CSV data. It then runs a query to produce a Pandas DataFrame.
import asyncio
import kaskada as kd
kd.init_session()
content = "\n".join(
[
"time,key,m,n",
"1996-12-19T16:39:57,A,5,10",
"1996-12-19T16:39:58,B,24,3",
"1996-12-19T16:39:59,A,17,6",
"1996-12-19T16:40:00,A,,9",
"1996-12-19T16:40:01,A,12,",
"1996-12-19T16:40:02,A,,",
]
)
source = await kd.sources.CsvString.create(content, time_column="time", key_column="key")
source.select("m", "n").extend({"sum_m": source.col("m").sum()}).to_pandas()
| 0 |
1996-12-19 16:39:57 |
A |
5 |
5.0 |
10.0 |
| 1 |
1996-12-19 16:39:58 |
B |
24 |
24.0 |
3.0 |
| 2 |
1996-12-19 16:39:59 |
A |
22 |
17.0 |
6.0 |
| 3 |
1996-12-19 16:40:00 |
A |
22 |
NaN |
9.0 |
| 4 |
1996-12-19 16:40:01 |
A |
34 |
12.0 |
NaN |
| 5 |
1996-12-19 16:40:02 |
A |
34 |
NaN |
NaN |