
import pandas as pd
import matplotlib.pylab as plt
import seaborn as sns
%matplotlib inline 
plt.style.use(['seaborn-dark']) # bmh Styling used for Visulization


df = pd.read_csv("Average Temperature of Cities.csv")
print ('Data read into a pandas dataframe!')

Data read into a pandas dataframe!


df.head() #Calling first 5 rows


table = pd.pivot_table(data=df,index='City')


table = table.reindex(columns=['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'])


table.head()


sns.set(rc = {'figure.figsize':(12,8)})
grid_kws = {"height_ratios": (.9, .05), "hspace": .3}
f, (ax, cbar_ax) = plt.subplots(2, gridspec_kw=grid_kws)
ax = sns.heatmap(table, ax=ax,cmap='seismic', annot=True,
                 cbar_ax=cbar_ax,
                 cbar_kws={"orientation": "horizontal"})
ax.set_title('Average Temperature of Cities', fontdict={'fontsize':18}, pad=12)

Text(0.5, 1.0, 'Average Temperature of Cities')


from pandas.plotting import parallel_coordinates


plt.figure(figsize = (12,8))
plt.title("Parallel Coordinates of Cities",fontsize = 18)
plt.xlabel("Month",fontsize = 14)
plt.ylabel("Temperature",fontsize = 14)
parallel_coordinates(df,'City',color=['blue','green','red'])
plt.show()


import folium


#fig2=Figure(width=550,height=350)
m2=folium.Map(location=[51.50585,-0.08580],zoom_start=15)
folium.TileLayer('Stamen Terrain').add_to(m2)
folium.TileLayer('Stamen Toner').add_to(m2)
folium.TileLayer('Stamen Water Color').add_to(m2)
folium.TileLayer('cartodbpositron').add_to(m2)
folium.TileLayer('cartodbdark_matter').add_to(m2)
folium.LayerControl().add_to(m2)
folium.Marker(location=[51.505852073619344, -0.08580355285735251],popup='London Bridge Bus Station (Stop A)',tooltip='Stop A').add_to(m2)
folium.Marker(location=[51.505184268753986, -0.08763818379407412],popup='London Bridge Bus Station (Stop D)',tooltip='Stop D').add_to(m2)
folium.Marker(location=[51.506112514864014, -0.08698372480495119],popup='London Bridge Bus Station (Stop R)',tooltip='Stop R').add_to(m2)
folium.Marker(location=[51.50685376256651, -0.08800296421424098],popup='London Bridge Bus Station (Stop Y)',tooltip='Stop Y').add_to(m2)
loc = [(51.505852073619344, -0.08580355285735251),
       (51.505184268753986, -0.08763818379407412),(51.506112514864014, -0.08698372480495119)]
loc2 = [(51.505852073619344, -0.08580355285735251),
       (51.506112514864014, -0.08698372480495119),(51.50685376256651, -0.08800296421424098)]
loc3 = [(51.50685376256651, -0.08800296421424098),
       (51.505184268753986, -0.08763818379407412),(51.506112514864014, -0.08698372480495119)]
folium.PolyLine(loc,
                color='red',
                weight=4,
                opacity=0.8).add_to(m2)
folium.PolyLine(loc2,
                color='Green',
                weight=2,
                opacity=0.8).add_to(m2)
folium.PolyLine(loc3,
                color='blue',
                weight=2,
                opacity=0.8).add_to(m2)
m2

	City	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
0	London	4.8	4.9	6.7	9.4	12.7	15.7	17.8	17.3	15.0	11.8	7.8	5.3
1	Paris	4.3	4.6	7.4	10.7	14.3	17.7	19.8	19.4	16.4	12.6	7.9	4.8
2	NewYork	-1.0	0.0	4.1	10.4	16.0	21.3	24.5	23.6	20.1	13.7	7.7	2.5

	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
City
London	4.8	4.9	6.7	9.4	12.7	15.7	17.8	17.3	15.0	11.8	7.8	5.3
NewYork	-1.0	0.0	4.1	10.4	16.0	21.3	24.5	23.6	20.1	13.7	7.7	2.5
Paris	4.3	4.6	7.4	10.7	14.3	17.7	19.8	19.4	16.4	12.6	7.9	4.8

Temperature Data Analysis¶

Importing Neccessary Libraries¶

Reading the Dataframe¶

Creating a pivot table for HeatMap (Task 1)¶

Creating HeatMap¶

Calling Library for Parallel Coordinates (Task 2)¶

Creating Parallel Coordinates Graph¶

Importing Folium to create Network Graph (Task 3)¶

Visualizing Graph¶