https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html
class pandas.DataFrame(data=None, index=None, columns=None, dtype=None, copy=None) [source] #. Two-dimensional, size-mutable, potentially heterogeneous tabular data. Data structure also contains labeled axes (rows and columns). Arithmetic operations align on both row and column labels. Can be thought of as a dict-like container for Series objects.

https://www.w3schools.com/python/pandas/pandas_dataframes.asp
Learn how to create, access, and manipulate Pandas DataFrames, a 2 dimensional data structure like a table with rows and columns. See examples, exercises, and certification options.

https://www.geeksforgeeks.org/python-pandas-dataframe/
Learn how to create, manipulate, and work with Pandas DataFrame, a two-dimensional tabular data structure with labeled axes. See examples of creating, selecting, indexing, and dealing with missing data in DataFrame.

https://realpython.com/pandas-dataframe/
Learn how to create, access, modify, and visualize data with pandas DataFrames, a two-dimensional data structure with labels. This tutorial covers data types, missing values, time series, and more.

https://pandas.pydata.org/docs/reference/frame.html
Learn how to create, manipulate and operate on DataFrame, a two-dimensional, size-mutable, potentially heterogeneous data structure in pandas. See attributes, methods, constructors, binary operators and examples of DataFrame.

https://pythonbasics.org/pandas-dataframe/
Pandas is a data manipulation module. DataFrame let you store tabular data in Python. The DataFrame lets you easily store and manipulate tabular data like rows and columns. A dataframe can be created from a list (see below), or a dictionary or numpy array (see bottom). Create DataFrame from list. You can turn a single list into a pandas

https://www.datacamp.com/tutorial/pandas-tutorial-dataframe-python
Learn how to create, manipulate and analyze data with pandas DataFrames, a powerful and flexible data structure in Python. This tutorial covers the basics, the index, the columns, the data types and more.

https://www.programiz.com/python-programming/pandas/dataframe
The DataFrame() function converts the 2-D list to a DataFrame. Each nested list behaves like a row of data in the DataFrame. The columns argument provides a name to each column of the DataFrame. Note: We can also create a DataFrame using NumPy array in a similar way. Pandas DataFrame From a File.

https://pandas.pydata.org/pandas-docs/stable/user_guide/basics.html
Learn how to create, access, and manipulate pandas data structures, such as Series and DataFrame. See examples of head, tail, shape, array, and to_numpy methods.

https://datagy.io/pandas/
Learn how to use pandas, a Python library for working with tabular data, in this comprehensive guide. You'll learn how to create, manipulate, and visualize DataFrames, the two-dimensional data structure in pandas.

https://www.w3schools.com/datascience/ds_python_dataframe.asp
Learn how to create, interpret and manipulate a data frame with Pandas, a Python library for data analysis. A data frame is a structured representation of data with columns and rows.

https://pynative.com/python-pandas-dataframe/
Learn how to create, manipulate and analyze data using pandas DataFrame, a two-dimensional data structure with potentially heterogeneous data. See examples of DataFrame creation from dict, CSV, list, and other sources, and how to customize, filter, join, group and sort DataFrame.

https://www.dataquest.io/blog/tutorial-how-to-create-and-use-a-pandas-dataframe/
Learn how to work with DataFrames, a flexible data structure for analyzing and manipulating data in Python. See how to import DataFrames from external files or create them from scratch with pandas library.

https://www.codecademy.com/resources/docs/pandas/dataframe
A DataFrame is the primary object used by the Pandas module to store and manipulate data. It is a structured collection of data arranged in rows and columns, similar to a database table. Many Pandas functions, such as .read_csv(), return DataFrame objects. Other functions take DataFrame objects and accept them as parameters. In addition, most of Pandas' functionality is implemented through

https://pandas.pydata.org/pandas-docs/stable/user_guide/10min.html
Learn the basics of pandas, a Python library for data analysis and manipulation. See how to create and view DataFrame objects, a two-dimensional data structure that holds data like a table.

https://stackoverflow.com/questions/11285613/selecting-multiple-columns-in-a-pandas-dataframe
To select multiple columns, extract and view them thereafter: df is the previously named data frame. Then create a new data frame df1, and select the columns A to D which you want to extract and view. df1 = pd.DataFrame(data_frame, columns=['Column A', 'Column B', 'Column C', 'Column D']) df1.

https://www.databricks.com/glossary/what-are-dataframes
DataFrames are 2-dimensional tables of rows and columns that can span distributed computing clusters. Learn how DataFrames are used in Spark, pandas, R, Scala, and other languages and frameworks.

https://www.databricks.com/glossary/pandas-dataframe
pandas DataFrame is a way to represent and work with tabular data. It can be seen as a table that organizes data into rows and columns, making it a two-dimensional data structure. A DataFrame can be created from scratch, or you can use other data structures, like NumPy arrays.

https://www.runoob.com/pandas/pandas-dataframe.html
介绍了 DataFrame 的概念、特点、构造方法和操作方法，以及如何使用列表、字典和 ndarray 创建 DataFrame 对象。DataFrame 是 Pandas 中的核心数据结构，用于表示二维表格型数据，可以进行数据访问、筛选、分割、合并、重塑、聚合等操作。

https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html
Learn how to create and manipulate Series, a one-dimensional labeled array, and DataFrame, a two-dimensional labeled array, in pandas. See examples of data types, indexing, alignment, and methods for both data structures.

https://www.tutorialspoint.com/python_pandas/python_pandas_dataframe.htm
A pandas DataFrame can be created using the following constructor −. pandas.DataFrame( data, index, columns, dtype, copy) The parameters of the constructor are as follows −. Sr.No. Parameter & Description. 1. data. data takes various forms like ndarray, series, map, lists, dict, constants and also another DataFrame. 2.

https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html
Learn how to slice, dice, and get subsets of pandas objects using different indexing methods and options. See examples of Series and DataFrame indexing with labels, positions, slices, callables, and more.

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.plot.html
pandas.DataFrame.plot. #. Make plots of Series or DataFrame. Uses the backend specified by the option plotting.backend. By default, matplotlib is used. The object for which the method is called. Only used if data is a DataFrame. Allows plotting of one column versus another. Only used if data is a DataFrame.