TV Guide with matplotlib

_.py

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime
from pandas import DataFrame
from matplotlib.ticker import FuncFormatter, MultipleLocator
from matplotlib.cm import ScalarMappable
from matplotlib.transforms import TransformedBbox, Bbox

# load dataframe
df = pd.read_csv("https://gist.githubusercontent.com/trnl/3611b2947d02d90452b0/raw/1d3552d6d4a07b68df79ec432a9d5a8bc522e77f/guide.csv")
# df = pd.read_csv("g.csv")
df['duration'] = df['end_time'] - df['start_time']

# get set of station names
st = df['station_title'].unique() 

fig, ax = plt.subplots()

# xaxis ticks formatting
ax.xaxis.set_major_formatter(FuncFormatter(lambda x,pos: datetime.fromtimestamp(x).strftime('%H:%M')))
ax.xaxis.set_major_locator(MultipleLocator(3600))
# ax.set_xlim(int(datetime(2014,12,31,21,0).strftime('%s')),int(datetime(201,12,31,21,0).strftime('%s'))

# yaxis ticks formatting
ax.set_yticks(np.arange(st.size))
ax.set_yticks(np.arange(st.size)+0.5,minor=True)
ax.set_yticklabels(st,minor=True)
for tick in ax.yaxis.get_major_ticks():
    tick.label1.set_visible(False) 

# colorbar
m = ScalarMappable(cmap = 'YlOrRd') 
m.set_array(df['view_count'])
plt.colorbar(m, ticks=np.linspace(df['view_count'].min(), df['view_count'].max(), num=10), label='Views', pad = 0.01)

def intersect(*args):
    return (max([x[0] for x in args]),min([x[1] for x in args]))

c = 0
for t in st:
    dfs = df[df['station_title']==t]

    bar = map(lambda (i,r): (r['start_time'],r['duration']), dfs.iterrows())
    colors = map(lambda (i,r): m.to_rgba(r['view_count']), dfs.iterrows())
    z = ax.broken_barh(bar, (c,1), facecolor=colors)
    for i,r in dfs.iterrows():
        xargs = intersect([r['start_time'],r['end_time']], ax.get_xlim())
        box = TransformedBbox(Bbox([[xargs[0],c],[xargs[1],c+1]]), ax.transData)
        ax.annotate(r['program_title'], xy=(r['start_time']+200,c+0.45), clip_box=box) # 200, 0.45 simple text alingments in the cell
    c += 1
plt.show()

figure.png

guide.csv