Data Visualization (Area Plots, Histograms, and Bar Plots)

Exploring Datasets with pandas and Matplotlib

We used pandas and Numpy for data wrangling, analysis, and visualization. The primary plotting library that we are exploring in the course is Matplotlib.

Dataset: Immigration to Canada from 1980 to 2013 - International migration flows to and from selected countries - The 2015 revision from United Nation's website.

Note: The dataset contains annual data on the flows of international migrants as recorded by the countries of destination. The data presents both inflows and outflows according to the place of birth, citizenship or place of previous / next residence both for foreigners and nationals. For this lesson, we will focus on the Canadian Immigration data.

1- Import data analysis modules: pandas and Numpy.

import numpy as np  # useful for many scientific computing in Python

import pandas as pd # primary data structure library

2- Read Data: 

df_can = pd.read_excel('https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DV0101EN-SkillsNetwork/Data%20Files/Canada.xlsx',

                        sheet_name='Canada by Citizenship',

                       skiprows=range(20),

                       skipfooter=2)

print ('Data read into a pandas dataframe!')

3- view the top 5 rows of the dataset using the head() function:

df_can.head()

# tip: You can specify the number of rows you'd like to see as follows: df_can.head(10) 

Waffle Charts

It is an interesting visualization that is normally created to display progress toward goals.

Word Clouds

is a depiction of the frequency of different words in some textual data.

Seaborn and Regression Plots

Is a python visualization library base on matplitlib, require less line of cod than matplotlib.

Code: 

import seaborn as sns

ax = sns.regplot(x = 'year', y = 'total', data = df_tot, color='green' , marker='+') //x : horizontal, y: vertical

Folium

 is a powerful Python library that helps you to create several types of leaflet maps. 

Code 

#define the world map

world_map = folium.Map()

#display world map

world_map

To create a Map of Canada

#define  the wold map centred around Canada with a low zoom level

world_map = folium.Map(location=[56.130, -106.35], zoom_start=4)

#display world map

wold_map

To create different Map Styles using Stamen Toner or Stamen Terrain

wold_map = folium.Map(location=[56.130, -106.35], zoom_start=4, tiles='Stamen Toner')

wold_map

Maps with Markers

Add a Marker or add circle mark to the center of city (Ontario)

#define  the wold map centred around Canada with a low zoom level

world_map = folium.Map(location=[56.130, -106.35], zoom_start=4)

#create Feature_group

Ontario = folium.map.FeatureGroup()

#style the feature group 

Ontario.add_child(folium.features.CirclMarker([51.25, -85.32], radius = 5, color='red', fill_color = 'Red"))

#add the feature group to the map

canada_map.add_child(ontario)

#label the marker

folium.Marker([51.25, -05.32], popup='Ontario').add_to(canada_map)

#display world map

wold_map

Choropleth Maps

is a thematic map in which areas are shaded or patterned in proportion to the measurement of the statistical variable being displayed on the map, such as population density or per capita income. 

Code: 

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