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There are multiple ways to add a new column to the existing DataFrame in Pandas. In this video, we're going to discuss all these ways in detail with live examples. So, let's get started.For implementation and code refer to: <a href="https://www.geeksforgeeks.org/python-pandas-dataframe-insert/">https://www.geeksforgeeks.org/python-pandas-dataframe-insert/</a>&nbsp;

How to Add New Column in Pandas Dataframe? | Pandas in Python

In this video, we're going to discuss how to handle missing values in Pandas. In Pandas DataFrame sometimes many datasets simply arrive with missing data, either because it exists and was not collected or it never existed. And as we can't provide null values to our Machine Learning model, we need to handle them properly. Now, let's get started.&nbsp;For implementation and code refer to: <a href="https://www.geeksforgeeks.org/working-with-missing-data-in-pandas/">https://www.geeksforgeeks.org/working-with-missing-data-in-pandas/</a>&nbsp;

Handling Missing Values in Pandas Dataframe | GeeksforGeeks How to Handle NULL values in Pandas Dataframe?

In this video, we're going to discuss how to remove or drop duplicate rows in Pandas DataFrame with the help of live examples. We will be using the Pandas drop_duplicates() method for removing duplicates from the data frame. So, let's get started.Check Out the Related Articles: https://www.geeksforgeeks.org/python-pandas-dataframe-drop_duplicates/

How to Remove Duplicate Rows in Pandas Dataframe? | Pandas in Python

Missing Data can occur when no information is provided for one or more items or for a whole unit. Missing Data is a very big problem in a real-life scenarios. Missing Data can also refer to as NA(Not Available) values in pandas.&nbsp;In DataFrame sometimes many datasets simply arrive with missing data, either because it exists and was not collected or it never existed.&nbsp;For Example, Suppose different users being surveyed may choose not to share their income, some users may choose not to share the address in this way many datasets went missing. &nbsp;In Pandas missing data is represented by two value:<ul><li>None: None is a Python singleton object that is often used for missing data in Python code.</li><li>NaN : NaN (an acronym for Not a Number), is a special floating-point value recognized by all systems that use the standard IEEE floating-point representation</li></ul> Related Article : &nbsp;<a href="https://www.geeksforgeeks.org/working-with-missing-data-in-pandas/">https://www.geeksforgeeks.org/working-with-missing-data-in-pandas/</a>

Handling Missing Values in Pandas Dataframe

Selecting rows based on particular column value using '&gt;', '=', '=', '&lt;=', '!=' operator.Code #1 : Selecting all the rows from the given dataframe in which ‘Percentage’ is greater than 80 using basic method.Code #2 : Selecting all the rows from the given dataframe in which ‘Percentage’ is greater than 80 using loc[].&nbsp;Related Article : &nbsp;<a href="https://www.geeksforgeeks.org/selecting-rows-in-pandas-dataframe-based-on-conditions/">https://www.geeksforgeeks.org/selecting-rows-in-pandas-dataframe-based-on-conditions/</a>

Selecting Rows in Pandas DataFrame Based on Conditions

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Pandas is one of those packages and makes importing and analyzing data much easier.&nbsp; Related Article : &nbsp;<a href="https://www.geeksforgeeks.org/different-ways-to-iterate-over-rows-in-pandas-dataframe/">https://www.geeksforgeeks.org/different-ways-to-iterate-over-rows-in-pandas-dataframe/</a>

Different Ways to Iterate Over Rows in Pandas DataFrame

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.Creating Pandas Dataframe can be achieved in multiple ways. Let’s see how can we create a Pandas DataFrame from Lists.Related Article : <a href="https://www.geeksforgeeks.org/create-a-pandas-dataframe-from-lists/">https://www.geeksforgeeks.org/create-a-pandas-dataframe-from-lists/</a>

Creating a Pandas DataFrame From Lists

Given a Pandas DataFrame, let’s see how to rename columns in Pandas with examples. Here, we will discuss 6 different ways to rename column names in pandas DataFrame.About Pandas DataFrame:&nbsp;Pandas DataFrame is a rectangular grid that is used to store data. It is easy to visualize and work with data when stored in dataFrame.<ul><li>It consists of rows and columns.</li><li>Each row is a measurement of some instance while the column is a vector that contains data for some specific attribute/variable.</li><li>Each Dataframe column has homogeneous data throughout any specific column but Dataframe rows can contain homogeneous or heterogeneous data throughout any specific row.</li><li>Unlike two-dimensional arrays, pandas’ Dataframe axes are labeled.</li></ul> Method 1: Using rename() functionOne way of renaming the columns in a Pandas Dataframe is by using the rename() function. This method is quite useful when we need to rename some selected columns because we need to specify information only for the columns which are to be renamed.&nbsp;Related Articles : &nbsp;<a href="https://www.geeksforgeeks.org/how-to-rename-columns-in-pandas-dataframe/">https://www.geeksforgeeks.org/how-to-rename-columns-in-pandas-dataframe/</a><a href="https://www.geeksforgeeks.org/rename-column-by-index-in-pandas/">https://www.geeksforgeeks.org/rename-column-by-index-in-pandas/</a>&nbsp;

How to Rename Columns in Pandas DataFrame

Let’s discuss how to add new columns to the existing DataFrame in Pandas. There are multiple ways we can do this task.Method #2: By using DataFrame.insert()It gives the freedom to add a column at any position we like and not just at the end. It also provides different options for inserting the column values.Related Article : &nbsp;<a href="https://www.geeksforgeeks.org/adding-new-column-to-existing-dataframe-in-pandas/">https://www.geeksforgeeks.org/adding-new-column-to-existing-dataframe-in-pandas/</a>

How to Add New Column in Pandas Dataframe

Let’s discuss how to drop one or multiple columns in Pandas Dataframe. To Delete a column from a Pandas DataFrame or Drop one or more than one column from a DataFrame can be achieved in multiple ways.Create a simple Dataframe with dictionary of lists, say column names are A, B, C, D, E. In this article, we will cover 6 different methods to delete some columns from Pandas DataFrame.Related &nbsp;Article : &nbsp;<a href="https://www.geeksforgeeks.org/how-to-drop-one-or-multiple-columns-in-pandas-dataframe/">https://www.geeksforgeeks.org/how-to-drop-one-or-multiple-columns-in-pandas-dataframe/</a>

How to Remove Columns From Pandas Dataframe

Pandas DataFrame is a 2-dimensional labeled data structure like any table with rows and columns. The size and values of the dataframe are mutable,i.e., can be modified. It is the most commonly used pandas object.&nbsp;Pandas DataFrame can be created in multiple ways. Let’s discuss different ways to create a DataFrame one by one.DataFrame() function is used to create a dataframe in Pandas. The syntax of creating dataframe is:pandas.DataFrame(data, index, columns)where,data: It is a dataset from which dataframe is to be created. It can be list, dictionary, scalar value, series, ndarrays, etc.index: It is optional, by default the index of the dataframe starts from 0 and ends at the last data value(n-1). It defines the row label explicitly.columns: This parameter is used to provide column names in the dataframe. If the column name is not defined by default, it will take a value from 0 to n-1. Related Article : &nbsp;<a href="https://www.geeksforgeeks.org/different-ways-to-create-pandas-dataframe/">https://www.geeksforgeeks.org/different-ways-to-create-pandas-dataframe/</a>

Different Ways to Create a Pandas DataFrame

Pandas drop_duplicates() method helps in removing duplicates from the <a href="https://www.geeksforgeeks.org/python-pandas-dataframe/">Pandas Dataframe</a> In <a href="https://www.geeksforgeeks.org/python-programming-language/">Python</a>.<h2 style="margin-left:0px;">Syntax of df.drop_duplicates()</h2>Syntax: DataFrame.drop_duplicates(subset=None, keep=’first’, inplace=False)Parameters:<ul><li>subset: Subset takes a column or list of column label. It’s default value is none. After passing columns, it will consider them only for duplicates.</li><li>keep: keep is to control how to consider duplicate value. It has only three distinct value and default is ‘first’.<ul><li>If ‘first‘, it considers first value as unique and rest of the same values as duplicate.</li><li>If ‘last‘, it considers last value as unique and rest of the same values as duplicate.</li><li>If False, it consider all of the same values as duplicates</li></ul></li><li>inplace: Boolean values, removes rows with duplicates if True.</li></ul>Return type: DataFrame with removed duplicate rows depending on Arguments passed.&nbsp;&nbsp;Related Article : &nbsp;<a href="https://www.geeksforgeeks.org/python-pandas-dataframe-drop_duplicates/">https://www.geeksforgeeks.org/python-pandas-dataframe-drop_duplicates/</a>

How to Remove Duplicate Rows in Pandas Dataframe

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