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DataFrame.drop(labels=None, *, axis=0, index=None, columns=None, level=None, inplace=False, errors='raise')[source] #. Drop specified labels from rows or columns. Remove rows or columns by specifying label names and corresponding axis, or by directly specifying index or column names.
16 lis 2012 · The best way to do this in Pandas is to use drop: df = df.drop('column_name', axis=1) where 1 is the axis number (0 for rows and 1 for columns.) Or, the drop() method accepts index / columns keywords as an alternative to specifying the axis. So we can now just do:
8 sie 2023 · The drop() method allows you to delete rows and columns from pandas.DataFrame. pandas.DataFrame.drop — pandas 2.0.3 documentation
Create a spreadsheet-style pivot table as a DataFrame. pop (item) Return item and drop from frame. pow (other[, axis, level, fill_value]) Get Exponential power of dataframe and other, element-wise (binary operator pow). prod ([axis, skipna, numeric_only, min_count]) Return the product of the values over the requested axis.
Definition and Usage. The drop() method removes the specified row or column. By specifying the column axis (axis='columns'), the . drop() method removes the specified column. By specifying the row axis (axis='index'), the . drop() method removes the specified row. Syntax. dataframe.drop (labels, axis, index, columns, level, inplace., errors)
DataFrame.drop (labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors='raise') [source] ¶ Drop specified labels from rows or columns. Remove rows or columns by specifying label names and corresponding axis, or by specifying directly index or column names.
8 lut 2024 · The drop () function in the Python pandas library is useful for removing specified rows or columns from a DataFrame or Series. The function takes in several parameters, including the labels to drop, the axis (i.e., rows or columns), and whether or not to modify the original DataFrame in place.
