1 files changed, 51 insertions(+), 0 deletions(-)

A tickets-per-month.py

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+#
+# How many tickers are issued in Boston per month?
+#
+import matplotlib.pyplot as plt
+
+import pandas as pd
+import numpy as np
+import utils
+
+months = range(1, 13)
+data = utils.data
+#data.info()
+
+# group all tickets by month
+bmo = data.groupby(pd.Grouper(key="Issued", freq="M"))["Issued"].count()
+fig, ax = plt.subplots()
+
+# discard 2020 data
+covid = bmo[bmo.index.year == 2020]
+bmo.drop(covid.index, inplace=True)
+
+# group year/month into month
+bmo2 = bmo.copy()
+bmo2.index =  bmo2.index.strftime("%m")
+
+# plot the average and standard deviation
+avg = bmo2.groupby(bmo2.index).median()
+# plt.plot(months, avg, color="black", alpha=0.5)
+
+# add standard deviation shading
+std = bmo2.groupby(bmo2.index).std()
+plt.fill_between(months, avg-std, avg+std, facecolor="white")
+
+# add each month-year total
+plt.scatter(bmo.index.month, bmo.values, color="black",
+            alpha=0.5, label="11-19")
+plt.scatter(covid.index.month, covid.values, color="tab:red",
+            alpha=0.5, label="2020")
+
+plt.legend(loc="lower left", framealpha=0.5)
+plt.xticks(months, ['J', 'F', 'M', 'A', 'M', 'J',
+                    'J', 'A', 'S', 'O', 'N', 'D'])
+
+ax.set(
+    title="Tickets Issued in each Month",
+    ylabel="Tickets Issued")
+
+plt.tight_layout()
+plt.savefig(
+    utils.FIG_DIR / "tickets-per-month.svg",
+    transparent=True)