Parameters index array-like, optional Pandas set_index() is the method to set a List, Series, or Data frame as an index of a DataFrame. Pandas set_index() is an inbuilt pandas work that is used to set the List, Series or DataFrame as a record of a Data Frame. This command can basically replace or expand the existing index columns. Set value to coordinates. sort_index (axis = 0, level = None, ascending = True, inplace = False, kind = 'quicksort', na_position = 'last', sort_remaining = True, ignore_index = False, key = None) [source] ¶ Sort object by labels (along an axis). pandas.DataFrame.set_index¶ DataFrame.set_index (keys, drop=True, append=False, inplace=False, verify_integrity=False) [source] ¶ Set the DataFrame index (row labels) using one or more existing columns. Function working inplace , it means it performs the operation and returns a copy of the object and also it return None , check b = b.reset_index(inplace=True, drop=True) and print (b) – jezrael Aug 14 '18 at 6:05 But sometimes, the data frame is made out of two or more data frames, and hence later, the index can be changed using the set_index… By default yields a new object. Pandas Set Index. reindex (index = None, ** kwargs) [source] ¶ Conform Series to new index with optional filling logic. Once we do this, we can reference rows by the index value (i.e., the “label”) associated with the particular row. Index column can be set while making the data frame too. pandas.DataFrame.set_index(keys, drop=True, append=False, inplace=False, verify_integrity=False) keys : label or array-like or list of labels/arrays – This parameter can be either a single column key, a single array of the same length as the calling DataFrame. python pandas. You should really use verify_integrity=True because pandas won't warn you if the column in non-unique, which can cause really weird behaviour. Places NA/NaN in locations having no value in the previous index. inplace=True parameter is possible use in more function in pandas and working same. 21.2k 21 21 gold badges 58 58 silver badges 112 112 bronze badges. Se above: Set value to individual cell Use column as index. It sets the index in the DataFrame with the available columns. ... just need to delete the old index and set up a new one, with the order of rows preserved. Share. I have a problem where I produce a pandas dataframe by concatenating along the row axis (stacking vertically). To set an existing column as index, use set_index(, verify_integrity=True): Let’s take a look at the different parameters you can pass pd.DataFrame.set_index(): keys: What you want to be the new index.This is either 1) the name of the DataFrame’s column or 2) A Pandas Series, Index, or NumPy Array of the same length as your DataFrame. The Pandas set_index method is the tool that we use to do this. pandas.DataFrame.sort_index¶ DataFrame. The Pandas set index method enables you to take one of the columns of a DataFrame and turn it into the index. Making the first (or n-th) row the index: df.set_index(df.iloc[0].values) You can use both if you want a multi-level index: df.set_index([df.iloc[0], df.columns[0]]) Observe that using a column as index will automatically drop it as column. Chris Chris. A new object is produced unless the new index is equivalent to the current one and copy=False. Follow asked Feb 20 '16 at 19:41. 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