by_month_by_category.py

def add_day_month_year(df):
    dates = df["Date"].map(lambda x: x[:10])
    df["day_of_month"] = dates.map(lambda x: x.split("/")[1])
    df["month"] = dates.map(lambda x: x.split("/")[0])
    df["year"] = dates.map(lambda x: x.split("/")[2])
    df["date"] = dates
    return df


from pandas import read_csv

crimes_df = read_csv("CrimeData.csv")
crimes_df = add_day_month_year(crimes_df)
crimes_df = crimes_df[crimes_df.year <= "2019"]
crimes_df = crimes_df[crimes_df.type == "BATTERY"] # "THEFT"...
days_df = read_csv("DaysData.csv")

crimes_count_df = crimes_df \
    .groupby(["year"]) \
    .size() \
    .to_frame("crimes") \
    .reset_index()

print(crimes_count_df.to_string())