Hướng dẫn dùng df rename python
Alter axes labels. Function / dict values must be unique (1-to-1). Labels not contained in a dict / Series will be left as-is. Extra labels listed don’t throw an error. See the user guide for more. Parametersmapperdict-like or functionDict-like or function transformations to apply to that axis’ values. Use either Alternative to specifying axis ( Alternative to specifying axis ( Axis to target with Also copy underlying data. inplacebool, default FalseWhether to return a new DataFrame. If True then value of copy is ignored. levelint or level name, default NoneIn case of a MultiIndex, only rename labels in the specified level. errors{‘ignore’, ‘raise’}, default ‘ignore’If ‘raise’, raise a KeyError when a dict-like mapper, index, or columns contains labels that are not present in the Index being transformed. If ‘ignore’, existing keys will be renamed and extra keys will be ignored. ReturnsDataFrame or NoneDataFrame with the renamed axis labels or None if If any of the labels is not found in the selected axis and “errors=’raise’”. Examples
We highly recommend using keyword arguments to clarify your intent. Rename columns using a mapping: >>> df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}) >>> df.rename(columns={"A": "a", "B": "c"}) a c 0 1 4 1 2 5 2 3 6 Rename index using a mapping: >>> df.rename(index={0: "x", 1: "y", 2: "z"}) A B x 1 4 y 2 5 z 3 6 Cast index labels to a different type: >>> df.index RangeIndex(start=0, stop=3, step=1) >>> df.rename(index=str).index Index(['0', '1', '2'], dtype='object') >>> df.rename(columns={"A": "a", "B": "b", "C": "c"}, errors="raise") Traceback (most recent call last): KeyError: ['C'] not found in axis Using axis-style parameters: >>> df.rename(str.lower, axis='columns') a b 0 1 4 1 2 5 2 3 6 >>> df.rename({1: 2, 2: 4}, axis='index') A B 0 1 4 2 2 5 4 3 6 |