![]() ![]() Removing index and columns names means set it to None: df2 = df.rename_axis(index=(None,None), columns=(None,None))Īnd solution: df.index. Plural is necessary for check/set values: print (df.index.name)ĭf2 = df.rename_axis(('baz','bak'), axis=1)ĭf2 = df.rename_axis(index=('foo','bar'), columns=('baz','bak')) For a larger data set we can slice the columns that we need and apply the below code: df.columns 'newname','newname1','oldname' Share. ![]() Mux2 = pd.om_product([list('ABC'),ĭf = pd.DataFrame(np.random.randint(10, size=(4,6)), index=mux1, columns=mux2) For renaming the columns here is the simple one which will work for both Default (0,1,2,etc ) and existing columns but not much useful for a larger data sets (having many columns). name and set by list or tuples: mux1 = pd.om_arrays(, renameaxis() Step 3: Rename Pandas index with df.index.names Step 4: Rename Pandas index with method df.index. Removing index and columns names means set it to None: df2 = df.rename_axis(index=(None,None), columns=None)įor MultiIndex in index and columns is necessary working with. Keep in mind that this produces a copy of the dataframe with renamed index values and should be assigned to a variable name in order to make it persist. If MultiIndex in index only: mux = pd.om_arrays(,ĭf = pd.DataFrame(np.random.randint(10, size=(4,6)),Ĭolumns=list('ABCDEF')).rename_axis('col name', axis=1)ĭf2 = df.rename_axis(index=('foo','bar'), columns='baz') Removing index and columns names means set it to None: df = df.rename_axis(index=None, columns=None) The following examples show how to use this sytnax in practice. inplace: Specifying True allows pandas to replace the index in the original DataFrame instead of creating a copy of the DataFrame. It provides two main data structures, Series and DataFrame, for storing and working with data. drop: Specifying True prevents pandas from saving the original index as a column in the DataFrame. Print df.rename_axis('foo').rename_axis("bar", axis=1)įrom version pandas 0.24.0+ is possible use parameter index and columns: df = df.rename_axis(index='foo', columns="bar") Pandas is a powerful library for data manipulation and analysis in Python. index.names: df.index. Print df.rename_axis('foo').rename_axis("bar", axis="columns") You are using a single index, therefore you can simple use. You can use rename_axis, for removing set to None: d = ĭf = pd.DataFrame(d).set_index('Index Title').rename_axis('Col Name', axis=1)
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