In [43]:

    

import pandas as pd
%matplotlib inline
import numpy as np
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
from plotly import graph_objs as go
init_notebook_mode(connected=True)


    

In [28]:

    

df = pd.read_csv('data/GLB.Ts+dSST.csv', skiprows=1)


    

In [45]:

    

df.info()


    

    




<class 'pandas.core.frame.DataFrame'>
RangeIndex: 138 entries, 0 to 137
Data columns (total 19 columns):
Year    138 non-null int64
Jan     138 non-null float64
Feb     138 non-null float64
Mar     138 non-null float64
Apr     138 non-null float64
May     138 non-null float64
Jun     138 non-null float64
Jul     138 non-null float64
Aug     137 non-null object
Sep     137 non-null object
Oct     137 non-null object
Nov     137 non-null object
Dec     137 non-null object
J-D     137 non-null object
D-N     136 non-null object
DJF     137 non-null object
MAM     138 non-null float64
JJA     137 non-null object
SON     137 non-null object
dtypes: float64(8), int64(1), object(10)
memory usage: 20.6+ KB

In [30]:

    

df.replace("***", np.nan, inplace=True)


    

In [31]:

    

df["SON"].map(float).plot()


    

    
Out[31]:





<matplotlib.axes._subplots.AxesSubplot at 0x107cc79e8>






    

In [47]:

    

trace = go.Scatter(
    x=df['Year'],
    y=df["SON"],
    name='Temperatures'
)
layout = go.Layout(
    title='Evolution of mean temperature during the year'
)
fig = go.Figure(
    data=[trace],
    layout=layout
)
iplot(fig)


    

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