+
+
+
+
+
+
+
+
+
+
+
+ 
import pandas as pd
+import gspread
+import matplotlib.pyplot as plt
+gc = gspread.service_account()
+
+sh = gc.open_by_key("1_tbwz6Z9uVZMJQZTysSQJYbSg-LCRdk6u49UngChM-Y")
+worksheet = sh.worksheet("Responses Raw")
+
+dataframe = pd.DataFrame(worksheet.get_all_records())
+dataframe["Incurring Month"] = pd.to_datetime(dataframe["Incurring Date"]).dt.strftime(
+ "%Y%m"
+)
+df_filtered = dataframe[~dataframe["Category"].isin(["Fake", "Travel"])]
+df_by_monthly = pd.pivot_table(
+ df_filtered,
+ index="Incurring Month",
+ columns="Category",
+ values="Amount of Money",
+ aggfunc=sum,
+)
+df_by_monthly.fillna(0)
+df_by_monthly_plot = df_by_monthly.plot.bar(stacked=True, figsize=(16, 9))
+df_by_monthly_plot.set_ylabel("Total Amount ($)")
+plt.xticks(rotation=45);
+
+df_travel = dataframe[
+ (dataframe["Category"] == "Travel") & (dataframe["Travel Tag"] != "")
+]
+df_travel_by_tag = pd.pivot_table(
+ df_travel,
+ index="Travel Tag",
+ columns="Travel Details",
+ values="Amount of Money",
+ aggfunc=sum,
+ margins=True,
+)
+df_travel_by_tag = (
+ df_travel_by_tag.sort_values(["All"], ascending=False)
+ .drop("All", axis=1)
+ .drop("All")
+)
+df_travel_by_tag.fillna(0)
+df_travel_by_tag_plot = df_travel_by_tag.plot.bar(stacked=True, figsize=(12, 8))
+df_travel_by_tag_plot.set_ylabel("Total Amount ($)")
+plt.xticks(rotation=45);
+
+
+