Plotting a Datetime Bar Graph with Pandas with different xlabels

Question

I would like to plot a bar graph that has only a few entries of data in each column of a pandas DataFrame with a bar graph. This is successful, but not only does it have the wro

Answer 1

Look at this code:

import pandas as pd
import numpy as np
from datetime import datetime 
import matplotlib.pylab as plt
from matplotlib.dates import DateFormatter

# Sample data
df_origin = pd.DataFrame(pd.date_range(datetime(2014,6,28,12,0,0), 
 datetime(2014,8,30,12,0,0), freq='1H'), columns=['Valid Time'])
df_origin = df_origin .set_index('Valid Time')
df_origin ['Precipitation'] = np.random.uniform(low=0., high=10., size=(len(df_origin.index)))
df_origin .loc[20:100, 'Precipitation'] = 0.
df_origin .loc[168:168*2, 'Precipitation'] = 0. # second week has to be dry

# Plotting
df_origin.plot(y='Precipitation',kind='bar',edgecolor='none',figsize=(16,8),linewidth=2, color=((1,0.502,0)))
plt.legend(prop={'size':16})
plt.subplots_adjust(left=.1, right=0.9, top=0.9, bottom=.1)
plt.title('Precipitation (WRF Model)',fontsize=24)
plt.ylabel('Hourly Accumulated Precipitation [mm]',fontsize=18,color='black')
ax = plt.gca()
plt.gcf().autofmt_xdate()

# skip ticks for X axis
ax.set_xticklabels([dt.strftime('%Y-%m-%d') for dt in df_origin.index])
for i, tick in enumerate(ax.xaxis.get_major_ticks()):
    if (i % (24*7) != 0): # 24 hours * 7 days = 1 week
        tick.set_visible(False)

plt.xlabel('Time',fontsize=18,color='black')

plt.show()