<jupyter_start><jupyter_text>0: NoCloud1: Cloud4: Fog6: Rain7: Snow11: Hail<jupyter_code>dfs['time']=pd.to_datetime(dfs['time'])
dfs['year']=dfs['time'].dt.year
dfs['month']=dfs['time'].dt.month
dfs['day']=dfs['time'].dt.day
dfs['hour']=dfs['time'].dt.hour
dfs=dfs.set_index('USAF')<jupyter_output><empty_output><jupyter_text>HU<jupyter_code>df=dfs.loc[[129250,128120,128050,127720,128220,128250,129350,129420,129600,129700,129820,129920,128600,
           128820,128920,128390,128430]]
df=df.set_index('time')
df=df.sort_index()
df['PCP06'].loc[~df['PCP06'].isnull()] = 6
dz=df[['PCP06','AW','MW','W']]
dz['AW']+=100
dz['MW']+=100
df['W']=dz.T.ffill().T['W'].replace(weather).replace(0,10)
df[['SPD','TEMP','SD','W','year','month','day','hour']].fillna(0).to_csv('data/hu.csv')<jupyter_output><empty_output><jupyter_text>RO<jupyter_code>df=dfs.loc[[152470,150800,152300,151200,150100,151700,152600,151450]]
df=df.reset_index().set_index('time')
df=df.sort_index()
df['PCP06'].loc[~df['PCP06'].isnull()] = 6
dz=df[['PCP06','AW','MW','W']]
dz['AW']+=100
dz['MW']+=100
df['W']=dz.T.ffill().T['W'].replace(weather).replace(0,10)
df[['SPD','TEMP','SD','W','year','month','day','hour']].fillna(0).to_csv('data/ro.csv')<jupyter_output><empty_output><jupyter_text>BP<jupyter_code>df=dfs.loc[[128390,128430]]
df=df.set_index('time')
df=df.sort_index()
df['PCP06'].loc[~df['PCP06'].isnull()] = 6
dz=df[['PCP06','AW','MW','W']]
dz['AW']+=100
dz['MW']+=100
df['W']=dz.T.ffill().T['W'].replace(weather).replace(0,10)
df[['SPD','TEMP','SD','W','year','month','day','hour']].fillna(0).to_csv('data/bp.csv')<jupyter_output><empty_output><jupyter_text>Exploration<jupyter_code>import matplotlib.pyplot as plt
%matplotlib inline
df.groupby(['W','year','USAF']).count().loc[6].loc[2011]<jupyter_output><empty_output><jupyter_text>New parser<jupyter_code>r=df.reset_index().set_index('USAF').loc[151200]
r=r.groupby(['year','month','day','time']).mean().reset_index().set_index('time')
r['TEMP'].plot()<jupyter_output><empty_output>
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