I have a CSV of financial data that is listed by:
- Date
- Category
- Amount
The dataset looks like the following, with another hundred rows. I am trying to use pandas to graph this data by month and then the total by each category. An example would be a bar graph of each month (Jan - Dec) with a bar for the total of each Category type (Food & Drink, Shopping, Gas).
Date Category Amount
0 12/29/2022 Food & Drink -28.35
1 12/30/2022 Shopping -12.12
2 11/30/2022 Food & Drink -12.30
3 11/30/2022 gas -12.31
4 10/30/2022 Food & Drink -6.98
....
My initial code worked, but totaled everything in the month and didn't separate by category type.
df['Transaction Date'] = pd.to_datetime(df['Transaction Date'], format='%m/%d/%Y') df = df.groupby(df['Transaction Date'].dt.month)['Amount'].sum()
My next try to separate the monthly information out by Category failed.
df = df.groupby((df['Transaction Date'].dt.month),['Category'])['Amount'].sum()
How can I graph out each month by the sum of Category type?
Here is an example. 
CodePudding user response：
You can create a new column for months within the data frame and then groupby months and category columns
df['Months'] = df['Transaction Date'].dt.month_name()
df = df.groupby(['Months', 'Category']).agg({'Amount':'sum'})