i've generated this dataframe:
np.random.seed(123)
len_df = 10
groups_list = ['A','B']
dates_list = pd.date_range(start='1/1/2020', periods=10, freq='D').to_list()
df2 = pd.DataFrame()
df2['date'] = np.random.choice(dates_list, size=len_df)
df2['value'] = np.random.randint(232, 1532, size=len_df)
df2['group'] = np.random.choice(groups_list, size=len_df)
df2 = df2.sort_values(by=['date'])
df2.reset_index(drop=True, inplace=True)
date group value
0 2020-01-01 A 652
1 2020-01-02 B 1174
2 2020-01-02 B 1509
3 2020-01-02 A 840
4 2020-01-03 A 870
5 2020-01-03 A 279
6 2020-01-04 B 456
7 2020-01-07 B 305
8 2020-01-07 A 1078
9 2020-01-10 A 343
I need to get rid of duplicated groups in the same date. I just want that one group appears only once in a date.
Result
date group value
0 2020-01-01 A 652
1 2020-01-02 B 1174
2 2020-01-02 A 840
3 2020-01-03 A 870
4 2020-01-04 B 456
5 2020-01-07 B 305
6 2020-01-07 A 1078
7 2020-01-10 A 343
.drop_duplicates() is in the pandas library and allows you to do exactly that. Read more in the documentation.
df2.drop_duplicates(subset=["date", "group"], keep="first")
Out[9]:
date group value
0 2020-01-01 A 652
1 2020-01-02 B 1174
3 2020-01-02 A 840
4 2020-01-03 A 870
6 2020-01-04 B 456
7 2020-01-07 B 305
8 2020-01-07 A 1078
9 2020-01-10 A 343