text_plain_output_1.png image_output_1.png
import matplotlib.pyplot as plt

import pandas as pd

import seaborn as sns

path = '../input/'
state_ts = pd.read_csv(path + 'State_time_series.csv', parse_dates=['Date'])

missing = state_ts.isnull().sum().sum()
missing * 100 / (state_ts.shape[0] * state_ts.shape[1])

cnt = state_ts['RegionName'].value_counts().to_frame()

state_vise = state_ts.groupby(['RegionName']).median()
state_vise.shape

plt.figure(figsize=(14, 10))
sns.barplot(state_vise['DaysOnZillow_AllHomes'], state_vise.index, palette='magma')