[python] Pandas split DataFrame by column value

I have DataFrame with column Sales.

How can I split it into 2 based on Sales value?

First DataFrame will have data with 'Sales' < s and second with 'Sales' >= s

Using groupby you could split into two dataframes like

In [1047]: df1, df2 = [x for _, x in df.groupby(df['Sales'] < 30)]

In [1048]: df1
Out[1048]:
   A  Sales
2  7     30
3  6     40
4  1     50

In [1049]: df2
Out[1049]:
   A  Sales
0  3     10
1  4     20

Using "groupby" and list comprehension:

Storing all the split dataframe in list variable and accessing each of the seprated dataframe by their index.

DF = pd.DataFrame({'chr':["chr3","chr3","chr7","chr6","chr1"],'pos':[10,20,30,40,50],})
ans = [pd.DataFrame(y) for x, y in DF.groupby('chr', as_index=False)]

accessing the separated DF like this:

ans[0]
ans[1]
ans[len(ans)-1] # this is the last separated DF

accessing the column value of the separated DF like this:

ansI_chr=ans[i].chr