Plotting mean frequency
Lastly, we'll create a per-day average of the mentions of both hashtags and plot them across time. We'll first create proportions from the two boolean Series by the day, then we'll plot them.
matplotlib.pyplot has been imported as plt and ds_tweets has been loaded for you.
この演習はコースの一部です
Analyzing Social Media Data in Python
演習の手順
- Generate the mean number of tweets with the
pythoncolumn with.resample()and.mean()methods..resample()takes one argument,'1 d', to produce daily averages. - Do the same with the
rstatscolumn. - Plot a line for
#pythonusage withmean_python. Usemean_python.index.dayas the x-axis. - Do the same with
mean_rstats.
実践的なインタラクティブ演習
このサンプルコードを完成させて、この演習に挑戦してみましょう。
# Average of python column by day
mean_python = ____[____].____(____).____()
# Average of rstats column by day
mean_rstats = ____[____].____(____).____()
# Plot mean python by day(green)/mean rstats by day(blue)
plt.plot(____, ____, color = 'green')
plt.plot(____, ____, ____)
# Add labels and show
plt.xlabel('Day'); plt.ylabel('Frequency')
plt.title('Language mentions over time')
plt.legend(('#python', '#rstats'))
plt.show()