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I have a dataframe with below columns:
SectorName', 'Sector', 'ItemName', 'Item', 'Counterpart SectorName', 'Counterpart Sector', 'Stocks and TransactionsName', 'Stocks and Transactions', 'Units', 'Scale', 'Frequency', 'Date', 'Value'
How to delete column from df where column name ends with Name.
701
To drop duplicate columns from pandas DataFrame use df. T. drop_duplicates(). T , this removes all columns that have the same data regardless of column names.
Use pandas. DataFrame. drop() method to delete/remove rows with condition(s).
To find duplicate columns we need to iterate through all columns of a DataFrame and for each and every column it will search if any other column exists in DataFrame with the same contents already. If yes then that column name will be stored in the duplicate column set.
We can exclude one column from the pandas dataframe by using the loc function. This function removes the column based on the location. Here we will be using the loc() function with the given data frame to exclude columns with name,city, and cost in python.
You can filter by inverting (~) boolean mask for columns which not need delete with loc and str.endswith, also working str.contains with $ for match end of string:
cols = ['SectorName', 'Name Sector', 'ItemName', 'Item', 'Counterpart SectorName']
df = pd.DataFrame([range(5)], columns = cols)
print (df)
SectorName Name Sector ItemName Item Counterpart SectorName
0 0 1 2 3 4
print (~df.columns.str.endswith('Name'))
[False True False True False]
df1 = df.loc[:, ~df.columns.str.endswith('Name')]
df1 = df.loc[:, ~df.columns.str.contains('Name$')]
Or filter columns names first:
print (df.columns[~df.columns.str.endswith('Name')])
Index(['Sector', 'Item'], dtype='object')
df1 = df[df.columns[~df.columns.str.endswith('Name')]]
print (df1)
Name Sector Item
0 1 3
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