根据列值在python中打乱数据帧的行，使具有相同列值的行在一起？

Question

Here's the dataframe I have

fruits=pd.DataFrame()
fruits['month']=['jan','feb','feb','march','jan','april','april','june','march','march','june','april']
fruits['fruit']=['apple','orange','pear','orange','apple','pear','cherry','pear','orange','cherry','apple','cherry']
fruits['price']=[30,20,40,25,30 ,45,60,45,25,55,37,60]

fruits

The rows in the dataframe should be shuffled, but the rows with the same month should appear together. In other words the rows in the dataframe should be shuffled based on the month and then the rows with the same month should be reshuffled amongst one another(2 level shuffle).

the output data frame should look something like this:

fruits_new=pd.DataFrame()
fruits_new['month']=['april','april','april','feb','feb','jan','jan','march','march','march','jun','jun']
fruits_new['fruit']=['cherry','pear','cherry','pear','orange','apple','apple','orange','orange','cherry','pear','apple']
fruits_new['price']=[60,45,60,40,20,30,30,25,25,55,45,37]

fruits_new

Answer 1

You can use pandas.DataFrame.sample and use fraction as 1, it will randomly take the sample from the dataframe rows, and frac=1 will make it take all the rows.

>>> df.sample(frac=1)

SAMPLE RUN:

#Initial dataframe
   0  1  2
0  5  6  A
1  5  8  B
2  6  6  C
3  6  9  D
4  5  8  E

>>> df.sample(frac=1)
#After shuffle
   0  1  2
0  5  6  A
4  5  8  E
1  5  8  B
3  6  9  D
2  6  6  C