117 lines
3.3 KiB
Python
117 lines
3.3 KiB
Python
import sqlite3
|
|
from pprint import pprint
|
|
import matplotlib.pyplot as plt
|
|
import numpy as np
|
|
from datetime import datetime
|
|
from collections import defaultdict
|
|
|
|
def weakness_by_hours(hours):
|
|
keys = list(hours.keys())
|
|
keys.sort()
|
|
|
|
for key in keys:
|
|
print(key, len(hours.get(key)))
|
|
|
|
|
|
fig, ax = plt.subplots()
|
|
ax.tick_params(axis='x', labelrotation=45)
|
|
hour_list = keys
|
|
counts = [len(hours.get(key)) for key in hours]
|
|
ax.bar(hour_list, counts)
|
|
ax.set_ylabel("moments of weakness")
|
|
ax.set_title("akshay's moments of weakness")
|
|
plt.show()
|
|
|
|
class Weakness:
|
|
def __init__(self, row):
|
|
self.name = row[0]
|
|
try:
|
|
self.time = datetime.fromisoformat(row[1])
|
|
except:
|
|
self.time = datetime.today()
|
|
self.total = row[2]
|
|
|
|
def weaknessInAnHour(results):
|
|
weaknesses = [Weakness(row) for row in results]
|
|
restaurants = defaultdict(lambda: 0)
|
|
|
|
for weakness in weaknesses:
|
|
if weakness.time.hour == 0:
|
|
restaurants[weakness.name] += 1
|
|
|
|
print(restaurants)
|
|
|
|
fig, ax = plt.subplots()
|
|
plt.xticks(rotation=45, ha='right')
|
|
ax.bar(restaurants.keys(), restaurants.values())
|
|
plt.show()
|
|
|
|
def weaknessPerMonth(results):
|
|
weaknesses = [Weakness(row) for row in results]
|
|
months = defaultdict(lambda: 0)
|
|
for weakness in weaknesses:
|
|
months[weakness.time.month] += weakness.total
|
|
|
|
fig, ax = plt.subplots()
|
|
sorted_keys = list(months.keys())
|
|
sorted_keys.sort()
|
|
sorted_amounts = [months.get(key) for key in sorted_keys]
|
|
ax.bar(sorted_keys, sorted_amounts)
|
|
plt.show()
|
|
|
|
def weaknessPerDayOverYear(results):
|
|
weaknesses = [Weakness(row) for row in results]
|
|
months = defaultdict(lambda: 0)
|
|
|
|
|
|
|
|
week_array = [[0] * 7 for x in range(53)]
|
|
|
|
for weakness in weaknesses:
|
|
week = weakness.time.isocalendar().week - 1
|
|
day = weakness.time.isocalendar().weekday - 1
|
|
week_array[week][day] += weakness.total
|
|
|
|
week_array = np.flipud(np.rot90(np.array(week_array)).round().astype(int))
|
|
fig, ax = plt.subplots()
|
|
im = ax.imshow(week_array, cmap="Reds")
|
|
|
|
ax.set_yticks(np.arange(7), labels=["Sunday", "Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday"])
|
|
ax.set_xticks(np.arange(53), labels=[
|
|
"", "Jan", "", "", "",
|
|
"Feb", "", "", "",
|
|
"", "Mar", "", "", "",
|
|
"Apr", "", "", "",
|
|
"", "May", "", "", "",
|
|
"Jun", "", "", "",
|
|
"Jul", "", "", "",
|
|
"Aug", "", "", "",
|
|
"", "Sep", "", "", "",
|
|
"Oct", "", "", "",
|
|
"", "Nov", "", "", "",
|
|
"Dec", "", "", "",
|
|
])
|
|
#[ f"Week {x+1}" for x in range(53)])
|
|
|
|
plt.setp(ax.get_xticklabels(), rotation=45, ha="right",
|
|
rotation_mode="anchor")
|
|
for i in range(53):
|
|
for j in range(7):
|
|
pass
|
|
# text = ax.text(i, j, week_array[j, i],
|
|
# ha="center", va="center", color="0", fontsize=12)
|
|
|
|
|
|
ax.set_title("akshay weakness in 2022")
|
|
fig.tight_layout()
|
|
plt.show()
|
|
|
|
|
|
|
|
|
|
with sqlite3.connect("doordash.db") as connection:
|
|
c = connection.cursor()
|
|
results = c.execute("select STORE_NAME, DELIVERY_TIME, sum(cast(SUBTOTAL as decimal)) from doordash group by DELIVERY_TIME, STORE_NAME;")
|
|
|
|
weaknessPerDayOverYear(results)
|