In [24]:

    

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
import warnings
warnings.filterwarnings('ignore')


    

In [47]:

    

city_temp = pd.read_csv('data/GlobalLandTemperaturesByMajorCity.csv')
city_temp.head(5)


    

    
Out[47]:







  

    

      

      
dt
      
AverageTemperature
      
AverageTemperatureUncertainty
      
City
      
Country
      
Latitude
      
Longitude
    
  
  

    

      
0
      
1849-01-01
      
26.704
      
1.435
      
Abidjan
      
Côte D'Ivoire
      
5.63N
      
3.23W
    
    

      
1
      
1849-02-01
      
27.434
      
1.362
      
Abidjan
      
Côte D'Ivoire
      
5.63N
      
3.23W
    
    

      
2
      
1849-03-01
      
28.101
      
1.612
      
Abidjan
      
Côte D'Ivoire
      
5.63N
      
3.23W
    
    

      
3
      
1849-04-01
      
26.140
      
1.387
      
Abidjan
      
Côte D'Ivoire
      
5.63N
      
3.23W
    
    

      
4
      
1849-05-01
      
25.427
      
1.200
      
Abidjan
      
Côte D'Ivoire
      
5.63N
      
3.23W
    
  

In [48]:

    

city_temp = city_temp[['dt','City','AverageTemperature']]
city_temp['dt'] = pd.to_datetime(city_temp['dt'])
city_temp['year'] = city_temp['dt'].map(lambda x:x.year)
city_temp['month'] = city_temp['dt'].map(lambda x:x.month)
city_temp = city_temp[['year','month','City','AverageTemperature']]
def season_(month):
    if month >=3 and month <=5:
        return 'spring'
    elif month >=6 and month <=8:
        return 'summer'
    elif month >=9 and month <=11:
        return 'antumn'
    else:
        return 'winter'
city_temp['season'] = city_temp['month'].apply(season_)
city_temp.head(5)


    

    
Out[48]:







  

    

      

      
year
      
month
      
City
      
AverageTemperature
      
season
    
  
  

    

      
0
      
1849
      
1
      
Abidjan
      
26.704
      
winter
    
    

      
1
      
1849
      
2
      
Abidjan
      
27.434
      
winter
    
    

      
2
      
1849
      
3
      
Abidjan
      
28.101
      
spring
    
    

      
3
      
1849
      
4
      
Abidjan
      
26.140
      
spring
    
    

      
4
      
1849
      
5
      
Abidjan
      
25.427
      
spring
    
  

In [70]:

    

min_year = city_temp['year'].min()
max_year = city_temp['year'].max()
years = range(min_year, max_year + 1)

spring_temps = []
summer_temps = []
autumn_temps = []
winter_temps = []

for year in years:
    curr_years_data = city_temp[city_temp['year'] == year]
    spring_temps.append(curr_years_data[curr_years_data['season'] == 'spring']['AverageTemperature'].mean())
    summer_temps.append(curr_years_data[curr_years_data['season'] == 'summer']['AverageTemperature'].mean())
    autumn_temps.append(curr_years_data[curr_years_data['season'] == 'autumn']['AverageTemperature'].mean())
    winter_temps.append(curr_years_data[curr_years_data['season'] == 'winter']['AverageTemperature'].mean())

sns.set(style="whitegrid")
sns.set_color_codes("deep")
f, ax = plt.subplots(figsize=(10, 6))

plt.plot(years, summer_temps, label='Summer average temperature', color='b')
plt.plot(years, autumn_temps, label='Autumn average temperature', color='r')
plt.plot(years, spring_temps, label='Spring average temperature', color='g')
plt.plot(years, winter_temps, label='Winter average temperature', color='orange')

plt.xlim(min_year, max_year)

ax.set_ylabel('Average temperature')
ax.set_xlabel('Year')
ax.set_title('Average temperature in each season')
legend = plt.legend(loc='center left', bbox_to_anchor=(1, 0.5), frameon=True, borderpad=1, borderaxespad=1)


    

In [ ]: