Description
Feature Type
-
Adding new functionality to pandas
-
Changing existing functionality in pandas
-
Removing existing functionality in pandas
Problem Description
The method of obtaining a certain cell or slice of the dataframe is confusing and unclear, such as using loc
, iloc
, at
, iat
, and the operator []
, etc. For example, df.loc[row_label, col_label]
and df.iloc[row_index, col_index]
. If loc
is a property, it is better to be a variable but now it is a verb or something rather than a df buffer. The user wants to take the cell value, so the behavior of loc
is like a member function and the ()
operator should be used to pass parameters. However, you are using the operator []
, but the object of the operator []
is usually an instance, which is a confusing place.
And when taking two columns or slices at the same time, for example, taking one column and one row, the expression value = df.loc[1, 'B']
, where the operator []
represents the horizontal and vertical coordinate information, and taking two columns and one row, row_data = df.loc['row_label', ['col1', 'col2']]
, where the second operator []
has both vertical coordinate information but behaves like a list
or tuple
instead of the former, this is another confusing aspect.
In mathematics, the coordinate values such as (3, 4) represent the horizontal and vertical coordinates respectively, as well as the ()
operator. I hope that the operation rules you define should conform to common customs or competition analysis or benchmarking such as numpy. thank you.
Feature Description
n/a
Alternative Solutions
n/a
Additional Context
No response