Pandas DataFrame: Difference between revisions
Jump to navigation
Jump to search
(→iloc[]) |
No edit summary |
||
| Line 5: | Line 5: | ||
=Internal= | =Internal= | ||
* [[Pandas_Concepts#DataFrame|Pandas Concepts]] | * [[Pandas_Concepts#DataFrame|Pandas Concepts]] | ||
* [[ | * [[Pandas_Series|Series]] | ||
=Overview= | =Overview= | ||
A DataFrame is a two-dimensional data structure with columns of potentially different types. The data structure also contains labeled axes, for both rows and columns. | A DataFrame is a two-dimensional data structure with columns of potentially different types. The data structure also contains labeled axes, for both rows and columns. | ||
Can be thought of as a dict-like container for [[ | Can be thought of as a dict-like container for [[Pandas_Series#Overview|Series]] objects, where each column is a [[Pandas_Series#Overview|Series]]. The dimensionality of the DataFrame is given by its <code>[[#Shape|shape]]</code> property. | ||
=Shape= | =Shape= | ||
Revision as of 18:36, 8 October 2023
External
- https://pandas.pydata.org/docs/user_guide/dsintro.html#dataframe
- https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.html#pandas.DataFrame
Internal
Overview
A DataFrame is a two-dimensional data structure with columns of potentially different types. The data structure also contains labeled axes, for both rows and columns.
Can be thought of as a dict-like container for Series objects, where each column is a Series. The dimensionality of the DataFrame is given by its shape property.
Shape
shape is a property of the DataFrame, containing a tuple that returns the dimensionality of the DataFrame: rows, columns.
Create a DataFrame
Create a DataFrame from a CSV File
Accessing Elements of a DataFrame
iloc[]
A property that allows integer-based access (indexing).
loc[]
A property that allows label-based access (indexing).