Pandas DataFrame is a 2-dimensional labeled data structure with columns of potentially different types. It is generally the most commonly used pandas object.
Pandas DataFrame can be created in multiple ways. Let’s discuss different ways to create a DataFrame one by one.
Method #1: Creating Pandas DataFrame from lists of lists.
Method #2: Creating DataFrame from dict of narray/lists
To create DataFrame from dict of narray/list, all the narray must be of same length. If index is passed then the length index should be equal to the length of arrays. If no index is passed, then by default, index will be range(n) where n is the array length.
Method #3: Creates a indexes DataFrame using arrays.
Method #4: Creating Dataframe from list of dicts
Pandas DataFrame can be created by passing lists of dictionaries as a input data. By default dictionary keys taken as columns.
Another example to create pandas DataFrame by passing lists of dictionaries and row indexes.
Another example to create pandas DataFrame from lists of dictionaries with both row index as well as column index.
Method #5: Creating DataFrame using
Two lists can be merged by using
list(zip()) function. Now, create the pandas DataFrame by calling
Method #6: Creating DataFrame from Dicts of series.
To create DataFrame from Dicts of series, dictionary can be passed to form a DataFrame. The resultant index is the union of all the series of passed indexed.
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