#!/usr/bin/env python
# coding: utf-8

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import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
get_ipython().run_line_magic('config', "InlineBackend.figure_format='retina'")


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df = pd.read_csv("austin_bikeshare_20191101.csv")


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df['start_time'] = pd.to_datetime(df['start_time'])
df['start_date'] = df['start_time'].dt.date
df['start_hour'] = df['start_time'].dt.hour


# In[4]:


date = '2019-11-05'
print(date)


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filter_df = df[df['start_date'].astype(str) == date]


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filter_df.head()


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filter_df.groupby(['start_hour'])[['trip_id']].count().plot();


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filter_df.groupby(['subscriber_type'])[['trip_id']].count().plot.barh();


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filter_df.groupby(['start_station_id'])['start_station_id'].count().plot.barh(figsize=(20, 10));


# In[10]:


plt.figure(figsize=(12,8))
plt.title("start station id count per start hour")
sns.heatmap(filter_df.groupby(['start_hour', 'start_station_id'])[['start_station_id']].count().unstack(),
           lw=.5, annot=True, cmap='GnBu', fmt='g', annot_kws={'size':10});


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