During 300 days, I harvested every tweet containing the hashtags #surf, #kitesurf and #windsurf. Here is a map showing the localisation of these tweets. This projects is explained more in detail in the blog of the R graph gallery. This map is done using the Basemap library of python. See more example in the dedicated section of the Python Graph Gallery.
# Libraries import pandas as pd from mpl_toolkits.basemap import Basemap import matplotlib.pyplot as plt # Set the dimension of the figure my_dpi=96 plt.figure(figsize=(2600/my_dpi, 1800/my_dpi), dpi=my_dpi) # read the data (on the web) data = pd.read_csv('http://python-graph-gallery.com/wp-content/uploads/TweetSurfData.csv', sep=";") # Make the background map m=Basemap(llcrnrlon=-180, llcrnrlat=-65,urcrnrlon=180,urcrnrlat=80) m.drawmapboundary(fill_color='#A6CAE0', linewidth=0) m.fillcontinents(color='grey', alpha=0.3) m.drawcoastlines(linewidth=0.1, color="white") # prepare a color for each point depending on the continent. data['labels_enc'] = pd.factorize(data['homecontinent'])[0] # Add a point per position m.scatter(data['homelon'], data['homelat'], s=data['n']/6, alpha=0.4, c=data['labels_enc'], cmap="Set1") # copyright and source data info plt.text( -170, -58,'Where people talk about #Surf\n\nData collected on twitter by @R_Graph_Gallery during 300 days\nPlot realized with Python and the Basemap library', ha='left', va='bottom', size=9, color='#555555' ) # Save as png plt.savefig('#315_Tweet_Surf_Bubble_map1.png', bbox_inches='tight')
I love it! This is exactly what I was looking for, and it took me very long to figure out to get the size of the bubbles corresponding to something that I want.
It looks simple and beautiful!
Thank you for sharing the code!
Francis
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