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Pie Subplots for a Pivotted DataFrame which is created using bins.

Hi,

I am trying to work on Pie Subplots in a Plotly using python. I have a dataset where I need to plot multiple Pie Chart based on the bins which I created for the score range from a test. I am finding it very difficult to plot it in Plotly.

Below is the DataFrame which I could come up by working on the dataset using pandas.

Screen Shot 2020-05-16 at 2.17.15 PM

scores,0-2 score,2-5 score,5-10 score,10-20 score

Test,

tutorial_101,942,136,1,0

tutorial_201,524,21,0,0

tutorial_301,540,11,0,0

tutorial_401,541,15,2,0

tutorial_501,58,655,1,1

tutorial_601,514,18,0,0

tutorial_701,520,20,0,0

tutorial_801,0,180,3,0

tutorial_901,137,47,0,0

tutorial_1001,142,43,1,0

tutorial_1101,143,44,2,0

tutorial_1201,4,171,3,0

I could not figure out a way to plot the above Pivoted DataFrame in Plotly Pie Subplots.

Can someone please help?

Thanks in advance

Hi @rohini_l
Are you trying to do something like this? This pie is only for 0-2 scores. The biggest pie slice of 23.2% belongs to 0-2 score=942

If not, can you please explain how you want your pie charts to look like.

Adam

Thanks Adam, Actually I am looking Pie Chart for each Tutorial with the scores being the Values [‘0-2 scores’,‘2-5 scores’, ‘5-10 scores’, ‘10-20 scores’ … ]

Something like below ->

There might be a faster way of doing this. I’m not sure. But one way I found is melting your data with pandas and creating separate dataframes for each test/tutorial. I did it like this:

import pandas as pd
import plotly.io as pio
import plotly.graph_objects as go
from plotly.subplots import make_subplots

df = pd.read_csv("testing4.csv")
print(df[:5])
df = df.melt(id_vars=["test"], var_name="scores")
print(df[:5])
df = df.groupby(['test'])
dff = [df.get_group(x) for x in df.groups]
print(dff[0])
print(dff[1])

# Create subplots:
fig = make_subplots(rows=1, cols=2, specs=[[{'type':'domain'}, {'type':'domain'}]])
# Create subplots: for 12 tutorials you can do
# fig = make_subplots(rows=4, cols=3, specs=[[{'type':'domain'}, {'type':'domain'},{'type':'domain'},{'type':'domain'}
#                                             {'type':'domain'},{'type':'domain'},{'type':'domain'},{'type':'domain'},
#                                             {'type':'domain'},{'type':'domain'},{'type':'domain'},{'type':'domain'}]])

fig.add_trace(go.Pie(labels=dff[0]['scores'], values=dff[0]['value'], name="tutorial_101"),
              1, 1)
fig.add_trace(go.Pie(labels=dff[1]['scores'], values=dff[1]['value'], name="tutorial_102"),
              1, 2)

pio.show(fig)

How does this work for you.
Did you modify the original data frame I shared. For me it throws me an error:

KeyError: “The following ‘id_vars’ are not present in the DataFrame: [‘Test’]”

Thanks

Sorry. I used these columns names in side testing4.csv:

test 0-2 score 2-5 score 5-10 score 10-20 score
tutorial_101 942 136 1 0
tutorial_201 524 21 0 0