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df.rename has a parameter called columns that accepts dictionaries: df.rename(columns=dict(zip(df2["val1"], df2["val2"]))) Out: A7 B0 C3 D1 0 1 2 3 4 1 5 6 7 8 It returns a new DataFrame. You can either use inplace=True, or assign it back to the original DataFrame.
29 sie 2022 · You can use the following basic syntax to rename columns with a dictionary in pandas: #define dictionary some_dict = {' old_col1 ': ' new_col1 ', ' old_col2 ': ' new_col2 ', ' old_col3 ': ' new_col3 '} #rename columns in DataFrame using dictionary df. rename (columns=some_dict, inplace= True)
9 mar 2023 · Table of contents. The DataFrame.rename () function. Rename a single column. Rename multiple columns. Using rename with axis=’columns’ or axis=1. Rename columns in place. Rename column using a function. Use lambda expressions to rename. Rename columns by removing leading and trailing spaces. Rename all columns with a list.
26 cze 2024 · You can rename multiple columns in a Pandas DataFrame using a dictionary with old column names as keys and new column names as values passed to the rename() method. import pandas as pd # Example DataFrame df = pd.DataFrame({ 'A': [1, 2, 3], 'B': [4, 5, 6], 'C': [7, 8, 9] }) # Rename multiple columns df.rename(columns={'A': 'New_A', 'B': 'New_B ...
3 mar 2021 · To rename columns in a Pandas DataFrame, you have two options: using the rename () method or the columns attribute. The .rename () method allows you to pass in existing labels and the ones you want to use. The .columns attribute allows you to specify a list of values to use as column labels.
7 sie 2023 · You can rename (change) column and/or index names in a pandas.DataFrame by using the rename(), add_prefix(), add_suffix(), set_axis() methods or by directly updating the columns and/or index attributes. Similarly, you can rename index names of a pandas.Series.
You can use .replace. For example: >>> df = pd.DataFrame({'col2': {0: 'a', 1: 2, 2: np.nan}, 'col1': {0: 'w', 1: 1, 2: 2}}) >>> di = {1: "A", 2: "B"} >>> df. col1 col2. 0 w a. 1 1 2.
