How Data Science Answers Different Questions
The blog post starts here.
import pandas as pd
import numpy as np
data = pd.DataFrame(
data=np.random.normal(loc=0.0, scale=1.0, size=1000),
columns=["gaussian_var"])
data[:10]
| gaussian_var | |
|---|---|
| 0 | 0.366702 |
| 1 | 0.0247435 |
| 2 | 1.72854 |
| 3 | 0.343894 |
| 4 | -0.914733 |
| 5 | -0.186893 |
| 6 | -0.53095 |
| 7 | -0.660085 |
| 8 | -0.740802 |
| 9 | 1.55077 |
import altair as alt
alt.renderers.enable(
'altair_saver', fmts=['svg'],
embed_options={'scaleFactor': '1.5', 'theme': 'light'},
# method="selenium",
# webdriver="chrome",
)
alt.Chart(data).mark_bar().encode(
x=alt.X("gaussian_var", bin=alt.BinParams(maxbins=100)),
y="count()").properties(width=800)
