In [1]:

    

%matplotlib notebook
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd


    

In [3]:

    

data=pd.read_csv("05_temp_rain_v2.csv")
#data.columns
#data


    

In [4]:

    

pivot=data.pivot_table(["rain(mm)","temp(dC)"], ["loc","month"])
pivot.head()


    

    
Out[4]:






  

    

      

      

      
rain(mm)
      
temp(dC)
    
    

      
loc
      
month
      

      

    
  
  

    

      
Adria_-_Bellombra
      
1
      
41.314286
      
2.933333
    
    

      
2
      
41.552381
      
4.280952
    
    

      
3
      
49.152381
      
8.733333
    
    

      
4
      
60.342857
      
13.038095
    
    

      
5
      
67.590476
      
18.185714
    
  

In [9]:

    

#pivot.xs("Agna", level=0)
locations=pivot.index.get_level_values(0).unique()
print(locations)
months=pivot.index.get_level_values(1).unique()
print(months)
print(len(months))

for location in locations:
    #print(pivot.xs(location, level=0))
    
    split=pivot.xs(location)
    rain=split["rain(mm)"]
    temp=split["temp(dC)"]
    
    plt.subplots()
    rain.plot(kind="bar").legend()
    plt.plot(range(len(temp)), temp, "r", label=temp.name)
    plt.legend()


    

    




['Adria_-_Bellombra' 'Agna' 'Agordo']
[ 1  2  3  4  5  6  7  8  9 10 11 12]
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