df.loc[['B', 'A'], 'X'] B 3 A 1 Name: X, dtype: int64 Notice the dimensionality of the return object when passing arrays. i is an array as it was above, loc returns an object in which an index with …

There are three different inputs you can use for .loc. A string; A list of strings; Slice notation using strings as the start and stop values; Selecting a single row with .loc with a string. To select a …

Why do we use loc for pandas dataframes? it seems the following code with or without using loc both compiles and runs at a similar speed: %timeit df_user1 = df.loc[df.user_id=='5561'] 100 …

Jan 17, 2017 · i want to have 2 conditions in the loc function but the && or and operators dont seem to work.: df: business_id ratings review_text xyz 2 'very bad' xyz 1 '

Jul 2, 2019 · As a side note, filtering the data with .loc and then using replace is redundant: .replace({512:263}) will convert values 512 only, no need to select that values before with .loc. …

Select specific rows and/or columns using loc when using the row and column names. Select specific rows and/or columns using iloc when using the positions in the table. You can assign …

Jan 17, 2019 · I know I can do this with only two conditions and then multiple df.loc calls, but since my actual dataset is quite huge with many different values the variables can take, I'd like to …

.loc of a data frame selects all the elements located by indexed_rows and labeled_columns as given in its argument. Instead, .at selects particular element of a data frame positioned at the …

Mar 8, 2018 · Edit:-This solution does not use groupby but uses .loc . I believe that what you want is to set flag as '1' when both admit and discharge day are same and also when the Num1 is …

Dec 30, 2023 · ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all(). I would expect this to still work as using the in or a combination of …