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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 list called badcu that says [23770, 24572, 28773, ...] each value corresponds to a different "bad" customer. Then I have another dataframe, lets call it sales, so I want to drop all the records for the bad customers, the ones in the badcu list. If I do the following.
30 Σεπ 2021 · In this post, you learned different ways of creating a Pandas dataframe from lists, including working with a single list, multiple lists with the zip() function, multi-dimensional lists of lists, and how to apply column names and datatypes to your dataframe.
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.
11 Μαρ 2021 · Often you may want to convert a list to a DataFrame in Python. Fortunately this is easy to do using the pandas.DataFrame function, which uses the following syntax: pandas.DataFrame(data=None, index=None, columns=None, …)
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.
