Classify The Wind Direction In Several Classes

Here is my question. I have one dataframe df which contain two columns named date and wd. And the wd means the wind direction which range from (0~360). So, the df represent the wi

Solution 1:

A nice way to do these kind of things is by using numpy.digitize(). It takes an array of bins and values and returns the index into which bin each value falls. Use these indices in a matching string array to get what you want:

import numpy as np
import pandas as pd

df = pd.DataFrame({"wd": pd.Series([20.1,50,8.4,359,243,123])})

directions = np.array('N NNE NE ENE E ESE SE SSE S SSW SW WSW W WNW NW NNW N'.split())
bins = np.arange(11.25, 372, 22.5)
df['wd_stat'] = directions[np.digitize(df['wd'], bins)]
printdf

      wd wd_stat
0   20.1     NNE
1   50.0      NE
2    8.4       N
3  359.0       N
4  243.0     WSW
5  123.0     ESE

Solution 2:

You can use loc:

import pandas as pd

df = pd.DataFrame({"wd": pd.Series([20.1,50,8.4 ])})
print df
     wd
020.1150.028.4print (df.wd >= 11.25 ) & (df.wd < 33.75 )
0True1False2False
Name: wd, dtype: bool

df.loc[(df.wd >= 11.25 ) & (df.wd < 33.75 ), 'new'] = 'NNE'
df.loc[(df.wd >= 33.75 ) & (df.wd < 56.25 ), 'new'] = 'NE'print df
     wd  new020.1  NNE
150.0   NE
28.4  NaN