How to get the difference between two DataFrames. For example, I have 2 DataFrames
previous_asks = pd.DataFrame({'price':[1,2,3], 'amount':[10,20,30]})
current_asks = pd.DataFrame({'price':[1,2,3,4], 'amount':[11,20,30,40]})
I would like to receive
price':[1, 4], 'amount':[11,40]
Using pandas:
a1 = list(range(10))
a2 = list(range(5, 8))
b1 = list('abcdefghij')
b2 = list('efy')
df1 = pd.DataFrame({'price':a1, 'amount':b1})
df2 = pd.DataFrame({'price':a2, 'amount':b2})
dict_results = dict()
for col in df1:
dict_results[col] = df1.loc[~ df1[col].isin(df2[col].values), col].values
print('--', col, dict_results[col])
Gives:
-- amount ['a' 'b' 'c' 'd' 'g' 'h' 'i' 'j']
-- price [0 1 2 3 4 8 9]
Using python3:
set1 = set(a1)
set2 = set(a2)
print(set1 - set2)
Gives:
{0, 1, 2, 3, 4, 8, 9}
I would rather go with python3 here since I think it is much simpler/readable.
If you orignally have pandas dataframes I would convert those to set data
type, manipulate those and revert back to pd.Dataframe if necessary.
Also it is worth checking out the
unique()
method of a pd.Series.
