# What is a Dataframe?

**DataFrame**.

**DataFrame**is a 2-dimensional labeled data structure with columns of potentially different types. You can think of it like a spreadsheet or SQL table, or a dict of Series objects. It is generally the most commonly used pandas object.

Regarding this, what is a DataFrame in Python?

**Python** | **Pandas DataFrame**. **Pandas DataFrame** is two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). A **Data frame** is a two-dimensional data structure, i.e., data is aligned in a tabular fashion in rows and columns.

Subsequently, question is, what is the difference between DataFrame and series? **Series** is a type of list in **pandas** which can take integer values, string values, double values and more. **Series** can only contain single list with index, whereas **dataframe** can be made of more than one **series** or we can say that a **dataframe** is a collection of **series** that can be used to analyse the data.

Also to know, what does data frame mean?

A **data frame** is a table or a two-dimensional array-like structure in which each column contains values of one variable and each row contains one set of values from each column. Following are the characteristics of a **data frame**. The column names should be non-empty.

What is a DataFrame spark?

A **Spark DataFrame** is a distributed collection of data organized into named columns that provides operations to filter, group, or compute aggregates, and can be used with **Spark** SQL. **DataFrames** can be constructed from structured data files, existing RDDs, tables in Hive, or external databases.