ScaterPlot With Scrub Filter
Set Up
Before Starting make sure to have Observable-Jupyter and any other needed libraries installed in your local environment.
[10]:
from observable_jupyter import embed
import pandas as pd
import json
from palmerpenguins import load_penguins
Load and Format Data
[11]:
penguins_data = load_penguins()
penguins_data.head()
[11]:
| species | island | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g | sex | year | |
|---|---|---|---|---|---|---|---|---|
| 0 | Adelie | Torgersen | 39.1 | 18.7 | 181.0 | 3750.0 | male | 2007 |
| 1 | Adelie | Torgersen | 39.5 | 17.4 | 186.0 | 3800.0 | female | 2007 |
| 2 | Adelie | Torgersen | 40.3 | 18.0 | 195.0 | 3250.0 | female | 2007 |
| 3 | Adelie | Torgersen | NaN | NaN | NaN | NaN | NaN | 2007 |
| 4 | Adelie | Torgersen | 36.7 | 19.3 | 193.0 | 3450.0 | female | 2007 |
The following block of code structures the data into a format accepted by Observable.
[12]:
result = penguins_data.to_json(orient="records")
parsed = json.loads(result)
data = json.dumps(parsed, indent=4)
Formated_Data = json.loads(data)
Embed your data into the visualization
The ScaterPlot With Scrub Filter visualization consists of three cells:
vegaPetalsWidget : Desplays the graph
viewof sepalLengthLimits : Desplays the top scrub filter
viewof sepalWidthLimits : Desplays the bottom scrub filter
To make your visualization work you will need to access the input variables:
input_data : set equal to your structured data.
x_title : set to the title of the column containg the data you want on the x axis.
y_title : set to the title of the column containg the data you want on the y axis.
legend : set to the name of the column in your data that allows you to difrerentiate your data.
specified_feature_1 : Set to a value you want to filter by.
specified_feature_2 : Set to a value you want to filter by.
[13]:
embed(
'@rstorni/visualize-a-data-frame-with-observable-in-jupyter/2',
cells=['vegaPetalsWidget', 'viewof sepalLengthLimits', 'viewof sepalWidthLimits'],
inputs = {
'input_data' : Formated_Data,
'x_title' : "bill_length_mm",
'y_title' : "bill_depth_mm",
'legend' : 'species',
'specified_feature_1': "body_mass_g",
'specified_feature_2': "flipper_length_mm"
}
)
