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21 Δεκ 2018 · I'd like to remove a particular value from within a list in the pandas dataframe column. How do I go about this? df = pd.DataFrame({'A': ['a1', 'a2', 'a3'], 'B': [['b1', 'b2'], ['b1', 'b1'], ['b2']], 'C': [['c1', 'b1'], ['b3'], ['b2', 'b2']], 'D': ['d1', 'd2', 'd3']})
Assuming row b only contains one value, then you can try with the following using a list comprehension within a function, and then simply apply it: import pandas as pd a = [[1,2,3,4,5,6],[23,23,212,223,1,12]] b = [1,1] df = pd.DataFrame(zip(a,b), columns = ['a', 'b']) def removing(row): val = [x for x in row['a'] if x != row['b']] return val df ...
7 Απρ 2017 · I have a dataframe customers with some "bad" rows, the key in this dataframe is CustomerID. I know I should drop these rows. I have a list called badcu that says [23770, 24572, 28773, ...] each value corresponds to a different "bad" customer.
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.
30 Σεπ 2021 · Learn how to create a Pandas dataframe from lists, including using lists of lists, the zip() function, and ways to add columns and an index.
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.
Specific rows and columns can be removed from a DataFrame object using the drop () instance method. The drop method can be specified of an axis – 0 for columns and 1 for rows. Similar to axis the parameter, index can be used for specifying rows and columns can be used for specifying columns.
