Horizontal grouped Barplot with Bokeh using dataframe - python-3.x

Question

I have a Dataframe and I want to group by Type, and then Flag and plot a graph for count of ID and another graph grouped by Type , Flag and sum of Total column in Bokeh.
')
p.hbar(df,
plot_width=800,
plot_height=800,
label='Type',
values='ID',
bar_width=0.4,
group = ' Type', 'Flag'
legend='top_right')
[![Expected Graph ][2]][2]
If it's not possible with Bokeh what other package can I use to get a good looking graph( Vibrant colours with white background)

Answer 1

You can do this with the holoviews library, which uses bokeh as a backend.
import pandas as pd
import holoviews as hv
from holoviews import opts
hv.extension("bokeh")
df = pd.DataFrame({
"type": list("ABABCCAD"),
"flag": list("YYNNNYNY"),
"id": list("DEFGHIJK"),
"total": [40, 100, 20, 60, 77, 300, 60, 50]
})
# Duplicate the dataframe
df = pd.concat([df] * 2)
print(df)
type flag id total
0 A Y 1 40
1 B Y 2 100
2 A N 3 20
3 B N 4 60
4 C N 5 77
5 C Y 6 300
6 A N 7 60
7 D Y 8 50
Now that we have our data, lets work on plotting it:
def mainplot_hook(plot, element):
plot.state.text(
y="xoffsets",
x="total",
text="total",
source=plot.handles["source"],
text_align="left",
y_offset=9,
x_offset=5
)
def sideplot_hook(plot, element):
plot.state.text(
y="xoffsets",
x="count",
text="count",
source=plot.handles["source"],
text_align="left",
y_offset=9,
x_offset=5
)
# Create single bar plot for sum of the total column
total_sum = df.groupby(["type", "flag"])["total"].sum().reset_index()
total_sum_bars = hv.Bars(total_sum, kdims=["type", "flag"], vdims="total")
# Create our multi-dimensional bar plot
all_ids = sorted(df["id"].unique())
counts = df.groupby(["type", "flag"])["id"].value_counts().rename("count").reset_index()
id_counts_hmap = hv.Bars(counts, kdims=["type", "flag", "id"], vdims="count").groupby("type")
main_plot = (total_sum_bars
.opts(hooks=[mainplot_hook],
title="Total Sum",
invert_axes=True)
)
side_plots = (
id_counts_hmap
.redim.values(id=all_ids, flag=["Y", "N"])
.redim.range(count=(0, 3))
.opts(
opts.NdLayout(title="Counts of ID"),
opts.Bars(color="#1F77B4", height=250, width=250, invert_axes=True, hooks=[sideplot_hook]))
.layout("type")
.cols(2)
)
final_plot = main_plot + side_plots
# Save combined output as html
hv.save(final_plot, "my_plot.html")
# Save just the main_plot as html
hv.save(main_plot, "main_plot.html")
As you can see, the code to make plots in holoviews can be a little tricky but it's definitely a tool I would recommend you pick up. Especially if you deal with high dimensional data regularly, it makes plotting it a breeze once you get the syntax down.