# Loading in the pandas module import pandas as pd # Reading in the data deaths = pd.read_csv("datasets/deaths.csv") # Print out the shape of the dataset print(deaths.shape) # Printing out the first 5 rows print(deaths.head())

# Summarizing the content of deaths deaths.info() # Define the new names of your columns newcols = { "Death": "death_count", "X coordinate": "x_latitude", "Y coordinate": "y_longitude" } print(newcols) # Rename your columns deaths.rename(columns=newcols, inplace=True) # Describe the dataset deaths.describe()

# Create `locations` by subsetting only Latitude and Longitude from the dataset print(deaths) locations = deaths[["x_latitude","y_longitude"]] # Create `deaths_list` by transforming the DataFrame to list of lists deaths_list = locations.values.tolist() # Check the length of the list len(deaths_list)

# Plot the data on map (map location is provided) using folium and for loop for plotting all the points import folium map = folium.Map(location=[51.5132119,-0.13666], tiles='Stamen Toner', zoom_start=17) for point in range(0, len(deaths)): folium.CircleMarker(deaths_list[point], radius=8, color='red', fill=True, fill_color='red', opacity = 0.4).add_to(map) map

# Import the data pumps = pd.read_csv("datasets/pumps.csv") # Subset the DataFrame and select just ['X coordinate', 'Y coordinate'] columns locations_pumps = pumps[['X coordinate','Y coordinate']] # Transform the DataFrame to list of lists in form of ['X coordinate', 'Y coordinate'] pairs pumps_list = locations_pumps.values.tolist() # Create a for loop and plot the data using folium (use previous map + add another layer) map1 = map for point in range(0, len(pumps)): folium.Marker(pumps_list[point], popup=pumps['Pump Name'][point]).add_to(map1) map1

# Import the data the right way dates = pd.read_csv('datasets/dates.csv', parse_dates=['date']) # Set the Date when handle was removed (8th of September 1854) handle_removed = pd.to_datetime('1854/9/8') # Create new column `day_name` in `dates` DataFrame with names of the day dates['day_name'] = dates.date.dt.day_name() # Create new column `handle` in `dates` DataFrame based on a Date the handle was removed dates['handle'] = dates.date > handle_removed # Check the dataset and datatypes dates.info() # Create a comparison of how many cholera deaths and attacks there were before and after the handle was removed dates.groupby(['handle']).sum()

import bokeh from bokeh.plotting import output_notebook, figure, show output_notebook(bokeh.resources.INLINE) # Set up figure p = figure(plot_width=900, plot_height=450, x_axis_type='datetime', tools='lasso_select, box_zoom, save, reset, wheel_zoom', toolbar_location='above', x_axis_label='Date', y_axis_label='Number of Deaths/Attacks', title='Number of Cholera Deaths/Attacks before and after 8th of September 1854 (removing the pump handle)') # Plot on figure p.line(dates['date'], dates['deaths'], color='red', alpha=1, line_width=3, legend_label='Cholera Deaths') p.circle(dates['date'], dates['deaths'], color='black', nonselection_fill_alpha=0.2, nonselection_fill_color='grey') p.line(dates['date'], dates['attacks'], color='black', alpha=1, line_width=2, legend_label='Cholera Attacks') show(p)

# Based on John Snow's map and the data John Snow collected, what would you say? print("john snow knows something")