69 lines
2.0 KiB
Python
Executable File
69 lines
2.0 KiB
Python
Executable File
#!.venv/bin/python
|
|
from db_con import DbConnect
|
|
from matplotlib import pyplot as plt
|
|
from datetime import date
|
|
import csv
|
|
|
|
con = DbConnect("olx_data.db")
|
|
con.get_connection()
|
|
|
|
query = """
|
|
select * from olx_data;
|
|
"""
|
|
data = con.get_data(query)
|
|
|
|
dates = []
|
|
rent = []
|
|
sell = []
|
|
exchange = []
|
|
|
|
for i in data:
|
|
sell.append(i[3])
|
|
rent.append(i[4])
|
|
exchange.append(i[5])
|
|
dates.append(date.fromisoformat(i[6]))
|
|
|
|
if len(dates) >= 7:
|
|
plt.plot(dates[-7:], rent[-7:], label="wynajem")
|
|
plt.plot(dates[-7:], sell[-7:], label="sprzedaż")
|
|
plt.plot(dates[-7:], exchange[-7:], label="zamiana")
|
|
plt.xlabel("data")
|
|
plt.xticks(rotation=45)
|
|
plt.ylabel("ilość ogłoszeń")
|
|
plt.title("ogłoszenia o mieszkaniach na olx.pl (ostatnie 7 dni)")
|
|
plt.legend()
|
|
plt.savefig("week.jpg", bbox_inches="tight", dpi=150)
|
|
plt.cla()
|
|
|
|
if len(dates) >= 30:
|
|
plt.plot(dates[-30:], rent[-30:], label="wynajem")
|
|
plt.plot(dates[-30:], sell[-30:], label="sprzedaż")
|
|
plt.plot(dates[-30:], exchange[-30:], label="zamiana")
|
|
plt.xlabel("data")
|
|
plt.xticks(rotation=45)
|
|
plt.ylabel("ilość ogłoszeń")
|
|
plt.title("ogłoszenia o mieszkaniach na olx.pl (ostatnie 30 dni)")
|
|
plt.legend()
|
|
plt.savefig("month.jpg", bbox_inches="tight", dpi=150)
|
|
plt.cla()
|
|
|
|
if len(dates) >= 90:
|
|
threemonths.plot(dates[-90:], rent[-90:], label="wynajem")
|
|
threemonths.plot(dates[-90:], sell[-90:], label="sprzedaż")
|
|
threemonths.plot(dates[-90:], exchange[-90:], label="zamiana")
|
|
threemonths.xlabel("data")
|
|
threemonths.xticks(rotation=45)
|
|
threemonths.ylabel("ilość ogłoszeń")
|
|
threemonths.title("ogłoszenia o mieszkaniach na olx.pl (ostatnie 90 dni)")
|
|
threemonths.legend()
|
|
threemonths.savefig("threemonths.jpg", bbox_inches="tight", dpi=150)
|
|
|
|
cursor=con.connection.cursor()
|
|
cursor.execute("SELECT * FROM olx_data;")
|
|
with open("data.csv", "w") as datacsv:
|
|
csv_out = csv.writer(datacsv)
|
|
csv_out.writerow([d[0] for d in cursor.description])
|
|
for result in cursor:
|
|
csv_out.writerow(result)
|
|
cursor.close()
|