21 дек. 2017 г. · This gets all unique values from all columns in a dataframe into one set. unique_values = set() for col in df: unique_values.update(df[col])

25 мар. 2021 г. · Try: list = [i for i in pandas.read_excel("some_file.xlsx")["some data"] if i not in list] Note: A name error may arise if you use the name list.

20 дек. 2022 г. · You can split, explode, and use unique: list_A = df['A'].str.split(',\s*').explode().unique().tolist() Output: ['A1', 'B2', 'C', 'A2',

24 янв. 2021 г. · Lists aren't hashable keys, use a tuple instead and then convert to list [*map(list,df['hobbies'].map(tuple).unique())] output: [['pirates'], ['climbing', 'yoga

4 окт. 2022 г. · I want to get the unique labels: 'O' , 'B-l1' , and 'I-l2' . The idea is to remove all rows that are not annotated, meaning the only label in ...

17 окт. 2019 г. · Assuming each of the values in your dataframe are important, here's a technique I frequently use to "unpack lists".

18 мая 2018 г. · I'm trying to remove all columns from a pandas dataframe where there are fewer than 10 unique items in the column. However, some of my data is lists and I get ...

22 апр. 2021 г. · I would like to make a list summarizing the different strings, as [A,B,F,...]. I've used groupby with nunique(), but I don't need counting. How can I make the ...

25 нояб. 2019 г. · What is the most efficient way to convert a pandas dataframe into a list of unique tuple? In the code below I am trying to extract a list of tuples containing ...

15 нояб. 2020 г. · You can use df.explode then use GroupBy.unique here. df.explode('values').groupby('id')['values'].unique().reset_index()