I have Dataframe
Date Category Sum
2019-06-03 "25M" 34
2019-06-03 "25M" 60
2019-06-03 "50M" 23
2019-06-04 "25M" 67
2019-06-05 "50M" -90
2019-06-05 "50M" 100
2019-06-06 "100M" 6
2019-06-07 "25M" -100
2019-06-08 "100M" 67
2019-06-09 "25M" 450
2019-06-10 "50M" 600
2019-06-11 "25M" -9
2019-07-12 "50M" 45
2019-07-13 "50M" 67
2019-07-14 "100M" 130
2019-07-14 "50M" 45
2019-07-15 "100M" 100
2019-07-16 "25M" -90
2019-07-17 "25M" 700
2019-07-18 "25M" -9
First, I will group my date and Category with Sum so that I get the data frame like this.
df.groupby(["EntryDate","Category"]).agg({"NetProfit":"sum"}).reset_index()
Date Category Sum
2019-06-03 "25M" 94
2019-06-03 "50M" 23
2019-06-04 "25M" 67
2019-06-05 "50M" 10
2019-06-06 "100M" 6 ...and so on
I want to create plotly Time Series grouped bar graph so that it will show me 3 bars for "25M", "50M" and "100M" on the respective date in PLotly.