Lists and Maps Lab

My changes

added 2 code snippets to the readme and completed the lab and commited the index.ipynb filev(P.S. I really liked this lab, the result images were so cool:D)

Introduction

Ok, so now that we have a sense of how to read from a list and alter a list in Python, let's see how our knowledge of lists can help us in creating data visualizations by plotting maps.

Working with lists and maps

As we know, lists are used to store a collection of data. In describing a city, we can use lists to organize our data in all sorts of ways. For example, here is a list of neighborhoods in the city of Buenos Aires.

neighborhoods = ['Palermo', 'Ricoleta', 'Santelmo', 'Puerto Madero', 'Belgrano', 'La Boca']

Press shift + enter on this cell and all following code cells.

Assign the variable palermo to the first element of the neighborhoods list.

palermo = None

Now assign the variable la_boca to the last element of our list.

la_boca = None

Beyond the neighborhoods, another thing that we can think of representing as a collection are the coordinates of a city, latitude and longitude. Below, our coordinates list contains the coordinates for Buenos Aires. The first element is latitude and the second is longitude.

coordinates = [-34.6037, -58.3816]

Set ba_latitude to equal the latitude of Buenos Aires and set ba_longitude to the longitude of Buenos Aires.

ba_latitude = None

ba_longitude = None

Now let's see if we can display this as a map.

First we download a mapping library with pip. Remember a library is simply a tool comprised of code hosted somewhere else on the internet and which we download to use in our current project. Pip is another tool that allows us to easily download various Python libraries from the Internet.

!pip install folium

Press shift + enter on the above code, and our folium library is available to us. Now we just tell Python that we will be using folium in our codebase by writing import folium in the next cell. Once the import is complete we will be able to display some maps with the help of folium.

import folium
buenos_map = folium.Map([ba_latitude, ba_longitude])
buenos_map

All of that from a couple of lines of code. Let's understand it:

import folium
buenos_map = folium.Map([ba_latitude, ba_longitude])
buenos_map

Folium is a mapping library built on Python. We created a representation of a map, by referencing the folium.Map function and passing through a list. That list represents the latitude and longitude, just like we saw previously. The map object is stored as the variable buenos. Since buenos_map is the last line of a cell, the map is displayed.

Now we can also add a marker to this map. For now, let's start by adding a marker for our Buenos Aires coordinates.

buenos_marker = folium.Marker([ba_latitude, ba_longitude])
buenos_marker.add_to(buenos_map)

So we used the folium library to create a marker. We specified the coordinates of the marker as a list. Finally, we added the marker to our map with the add_to function.

Let's see our updated map! We see our map by referencing our buenos_map variable.

buenos_map

Great! Note that both the map object and the map marker are just stored as variables.

buenos_marker

And just like any other piece of data in Python, we can place this marker in a list, and then retrieve it from the list.

buenos_markers = [buenos_marker]

buenos_markers[0]

Recall our neighborhoods list from above. The coordinates in the markers below match the neighborhoods in our neighborhoods list, respectively.

neighborhoods = ['Palermo', 'Ricoleta', 'Santelmo', 'Puerto Madero', 'Belgrano', 'La Boca']
marker_one = folium.Marker([-34.5711, -58.4233])
marker_two = folium.Marker([-34.5895, -58.3974])
marker_three = folium.Marker([-34.6212, -58.3731])
marker_four = folium.Marker([-34.6177, -58.3621])
marker_five = folium.Marker([-34.603722,  -58.381592])
marker_six = folium.Marker([-34.6345, -58.3631])
neighborhood_markers = [marker_one, marker_two, marker_three, marker_four, marker_five, marker_six]

Assign la_boca_marker equal to the last marker.

la_boca_marker = None

Below, we will rewrite buenos_map variable to create a new map of Buenos Aires, but this time we will add la_boca_marker to the map and zoom in a bit using the zoom_start attribute.

import folium
buenos_map = folium.Map([ba_latitude, ba_longitude], zoom_start = 12)
la_boca_marker.add_to(buenos_map)
buenos_map

Now that we plotted la_boca_marker we don't need the marker anymore. So, let's remove this last element from our neighborhood_markers list.

neighborhood_markers.pop()

print(len(neighborhood_markers)) # 5
print(neighborhood_markers[-1] == marker_five) # True

Now assign recoleta_marker to the second marker in the neighborhood_markers list. This time, we won't reassign our buenos_map so we should expect both la_boca_marker and recoleta_marker to appear!

recoleta_marker = None

recoleta_marker.add_to(buenos_map)
buenos_map

Don't worry if this feels tedious and manual. When we get up to loops in Python, we will see how to easily plot all of the markers in our list.

for marker in neighborhood_markers:
    marker.add_to(buenos_map)
buenos_map

But that's a lesson for another day.

Simple Codes

import matplotlib.pyplot as plt

lyrics = "Ah, Ba Ba Ba Ba Barbara Ann Ba Ba Ba Ba Barbara Ann Oh Barbara Ann Take My Hand Barbara Ann You Got Me Rockin' And A-Rollin' Rockin' And A-Reelin' Barbara Ann Ba Ba Ba Barbara Ann Ba Ba Ba Ba Barbara Ann Ba Ba Ba Ba Barbara Ann"
list_of_lyric_words = lyrics.split(' ')
unique_words = set(list_of_lyric_words)

print('Total words in lyrics: ', len(list_of_lyric_words))
print('Number of unique words in lyrics: ', len(unique_words))
print('Percentage of unique words: ', len(unique_words)/len(list_of_lyric_words)*100)

unique_count = {}
for word in unique_words:
	count = 0
	for nWord in list_of_lyric_words:
		if word == nWord:
			count +=1

	unique_count[word]=count 

print(unique_count)

y_pos = [unique_count[key] for key in unique_count.keys()]
plt.bar(unique_count.keys(), y_pos, align='center', alpha=0.5)
plt.show()

neighborhoods = ['Palermo', 'Ricoleta', 'Santelmo', 'Puerto Madero', 'Belgrano', 'La Boca']
laboca = neighborhoods[-1]

# pip install folium
coordinates = [-43.23, -54.23]
import folium 

_map = folium.Map([coordinates[0], coordinates[1]])
_marker = folium.Marker([coordinates[0], coordinates[1]])
_marker.add_to(_map)
print(_map)
print(_marker)

Summary

In this lesson we saw how to select information from a list and then plot that information with maps. We saw that lists can make good arguments to methods, as they represent an ordered collection of information, like latitude followed by longitude. In just a few lessons we saw how to use Python to make visualizations with our data going forward.

License

nazaninsbr/py-lists-with-maps-data-science-intro-000

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