Interactive Data Visualization with Bokeh
George Boorman
Core Curriculum Manager, DataCamp
Categorical data is any data with a fixed number of options or labels.
Factors are another term for categorical variables
print(nba[["position", "team", "conference"]].head())
position team conference
0 PG OKC West
1 PG HOU West
2 PG BOS East
3 C NO West
4 SG TOR East
pos = nba.groupby("position")["points"].mean() pos = pos.sort_values("points", ascending=False)
fig = figure(x_range=pos["position"], x_axis_label="Position", y_axis_label="Points per Game") fig.vbar(x=pos["position"], top=pos["points"]) output_file(filename="sorted_plot.html") show(fig)
fig = figure(x_range=nba["position"], x_axis_label="Position", y_axis_label="Points per Game") fig.vbar(x=nba["position"], top=nba["points"],
width=0.9)
output_file(filename="padded_plot.html") show(fig)
fig = figure(x_range=nba['position'], x_axis_label="Position", y_axis_label="Points per Game") fig.vbar(x=nba["position"], top=nba["points"], width=0.9)
fig.xaxis.major_label_orientation = 45
output_file(filename="rotated_x_label_plot.html") show(fig)
positions = ["Point Guard", "Shooting Guard", "Small Forward", "Power Forward", "Center"] conferences = ["East", "West"]
factors = [("Point Guard", "East"), ("Point Guard", "West"), ("Shooting Guard", "East"), ("Shooting Guard", "West"), ("Small Forward", "East"), ("Small Forward", "West"), ("Power Forward", "East"), ("Power Forward", "West"), ("Center", "East"), ("Center", "West")]
from bokeh.models import FactorRange
fig = figure(x_range=FactorRange(*factors), y_axis_label="Points per Game")
fig.vbar(x=factors, top=nba["points"], width=0.9)
output_file(filename="grouped_bar_plot.html") show(fig)
Interactive Data Visualization with Bokeh