What is the easiest way to arrange string Month rows in Pandas

Question

I have a df with a month column which is string:

Month      Value     Details
January      10        H12
April        12        J11
June         13        K03
May          08        Y21

I need to arrange the month in from April to March model. Which is the easiest way to do this? Desired result:

Month      Value     Details
April        12        J11
May          08        Y21
June         13        K03
January      10        H12

Answer 1

If need solution which working correctly if missing some months and all months in list of dictionary use Series.map with Series.argsort and then change order by DataFrame.iloc :

d = {'April':1,'May':2,'June':3,'July':4,'January':12}

df = df.iloc[df['Month'].map(d).argsort()]
print (df)
     Month  Value Details
1    April     12     J11
3      May      8     Y21
2     June     13     K03
0  January     10     H12

Or use ordered categoricals :

#add another months
c = ['April','May','June','July','January']
df['Month'] = pd.Categorical(df['Month'], categories=c, ordered=True)

df = df.sort_values('Month')
print (df)
     Month  Value Details
1    April     12     J11
3      May      8     Y21
2     June     13     K03
0  January     10     H12

Answer 2

You can use df.loc or df.reindex :

In [2048]: new_order = ['April','May','June','January']

In [2051]: df.set_index('Month', inplace=True)

In [2071]: df.loc[new_order].reset_index()    
Out[2071]: 
     Month  Value Details
0    April     12     J11
1      May      8     Y21
2     June     13     K03
3  January     10     H12

OR

In [2051]: df.reindex(new_order, axis=0).reset_index() 
Out[2071]: 
         Month  Value Details
    0    April     12     J11
    1      May      8     Y21
    2     June     13     K03
    3  January     10     H12