I would like to make a bubble chart out of this dataframe that shows gaps or frequencies of missing values in data analysis.
Is it possible to list field names or categorical values on the x axis and the plot the number of missing by different locations on the y axis?
Or do I need to create subplots for each location?
|Targeted Start Date |Targeted End Date |Projected End Date
Location | ------------------- | ----------------- | -----------------
Q | 0 | 0 | 0
R | 6 | 7 | 113
V | 1 | 1 | 6
Z | 0 | 0 | 0
import altair as alt
import pandas as pd
import numpy as np
d1 = {'Location': ['Q', 'R', 'V', 'Z'], 'Targeted Start Date': [0, 6, 1 ,0], 'Targeted End Date': [0, 7, 1 ,0], 'Targeted End Date': [0, 113, 6 ,0]}
df = pd.DataFrame.from_dict(d1)
#df = df.set_index('Location')
print(df)
dfMelt = df.melt(id_vars='Location', value_name='MissingItemCnt', var_name='FieldName')
print(dfMelt)
alt.Chart(dfMelt).mark_point().encode(x = 'FieldName', y = 'Location', size = 'MissingItemCnt')