dt.py

from datetime import datetime
import csv
import pandas as pd
import matplotlib.pyplot as plt

fn = './redfin_2019-08-08-20-18-37.csv'
fn_mapped = './redfin_2019-08-08-20-18-37-mapped.csv'
df = []

with open(fn) as f:
    csv_reader = csv.reader(f)
    df = [row for row in csv_reader]


def _adjust_row(row):
    if row[1]:
        dt = datetime.strptime(row[1], '%B-%d-%Y')
    else:
        dt = datetime.now()

    result = [row[0], dt.strftime('%Y-%m-%d')]

    for r in row[2:]:
        result.append(r)

    return result


df_mapped = list(map(_adjust_row, df[1:]))
df_mapped.insert(0, df[0])

with open(fn_mapped, mode='w', newline='\n') as f:
    writer = csv.writer(f)
    writer.writerows(df_mapped)

series = pd.read_csv(fn_mapped,
                     infer_datetime_format=True,
                     index_col=0,
                     parse_dates=['SOLD DATE'])
series.sort_values(by='SOLD DATE')

plt.plot_date(series['SOLD DATE'], series['$/SQUARE FEET'])
plt.show()

plt.plot_date(series['SOLD DATE'], series['PRICE'])
plt.show()