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Use pd.Index to name an index (or column) from construction. Pandas has Index (MultiIndex) objects that accepts names. Passing those as index or column on dataframe construction constructs frames with named indices/columns. data = {'Column 1': [1,2,3,4], 'Index Title': ["Apples","Oranges","Puppies","Ducks"]}
pandas provides a suite of methods in order to have purely label based indexing. This is a strict inclusion based protocol. Every label asked for must be in the index, or a KeyError will be raised. When slicing, both the start bound AND the stop bound are included, if present in the index.
The index of a DataFrame is a series of labels that identify each row. The labels can be integers, strings, or any other hashable type. The index is used for label-based access and alignment, and can be accessed or modified using this attribute.
The MultiIndex object is the hierarchical analogue of the standard Index object which typically stores the axis labels in pandas objects. You can think of MultiIndex as an array of tuples where each tuple is unique.
Index labels: these are labels for rows that can be accessed through the .index attribute (e.g., my_series.index). To access a row using index labels, one uses the .loc[] operator. Note that what we call index labels are usually just referred to as the “index” in most documentation about pandas.
2 Φεβ 2024 · We can get the name of the index column of the DataFrame using the name attribute of the index column. import pandas as pd. my_df = pd.DataFrame( { "Applicant": ["Ratan", "Anil", "Mukesh", "Kamal"], "Hometown": ["Delhi", "Pune", "Dhangadi", "Kolkata"], "Score": [85, 87, 90, 89], }, .
In Pandas, an index refers to the labeled array that identifies rows or columns in a DataFrame or a Series. For example, Name Age City. 0 John 25 New York. 1 Alice 28 London. 2 Bob 32 Paris. In the above DataFrame, the numbers 0, 1, and 2 represent the index, providing unique labels to each row.
