Exploratory Data Analysis - Canadian Bikeshare Stations

Updated: 24 apr 2026

Imports¶

All requires Python libraries are imported below

Below are altair settings required to support plotting large datasets and customize appearance

_ = alt.data_transformers.enable("vegafusion")
_ = alt.renderers.set_embed_options(actions=False)

About¶

Perform EDA.

User Inputs¶

url = "https://vegafusion-datasets.s3.amazonaws.com/vega/movies_201k.parquet"

Get Data¶

%%time
df = pd.read_parquet(url)
df.head()

CPU times: user 158 ms, sys: 47.8 ms, total: 206 ms
Wall time: 427 ms

EDA¶

Distributions of Numerical Features¶

Show a bar chart of all movie ratings

chart = (
    alt.Chart(df)
    .mark_bar()
    .encode(
        alt.X("IMDB_Rating:Q", bin=alt.Bin(maxbins=75)),
        y="count()",
    )
)
chart

Relationships of Numerical Features¶

%%time
chart = alt.Chart(df).mark_rect().encode(
    alt.X('IMDB_Rating:Q', bin=alt.Bin(maxbins=60)),
    alt.Y('Rotten_Tomatoes_Rating:Q', bin=alt.Bin(maxbins=40)),
    alt.Color('count():Q', scale=alt.Scale(scheme='greenblue'))
)
chart

CPU times: user 843 μs, sys: 0 ns, total: 843 μs
Wall time: 848 μs