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While analyzing the real datasets that are often very huge in size, we might need to get the column names in order to perform certain operations. So, in this video, we're going to discuss how can we get the column names in Pandas Dataframe. There are various methods for doing it such as tolist(), sorted(), etc. Let's understand each of them with the help of live examples. 00:00 Let's Start 01:43 Simply Iterating Over Columns to Get the Columns Name 03:16 Using tolist() for Getting a List of Columns 04:00 Using sorted() for Getting a List of Columns Sorted in Alphabetical Order 04:34 Getting Columns Names from .csv file 05:55 Closing Notes Download Dataset From [🤍 Check Out the Related Articles: How to Get Column Names in Pandas Dataframe [🤍 Complete Pandas Tutorial [🤍 WISH TO CONTRIBUTE VIDEOS ON GEEKSFORGEEKS? Please submit this Google Form - 🤍 Our courses: 🤍 This video is contributed by Akshit Madan. Please Like, Comment, and Share the Video with your friends. #python #pandas #dataframe #datascience #pythonpandas #eda Install our Android App: 🤍 If you wish, translate into the local language and help us reach millions of other geeks: 🤍 Follow us on our Social Media Handles - Twitter- 🤍 LinkedIn- 🤍 Facebook- 🤍 Instagram- 🤍 Reddit- 🤍 Telegram- 🤍 Also, Subscribe if you haven't already! :)
In this video we discuss the best way of getting a list of column names from a pandas dataframe. We go over how to get the column names as a list, tuples, and set. WE also examine the most performant method of returning a list of column names from your dataframe. ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Python & Data Merch - I think this is pretty cool stuff let me know what you think! 🤍 ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ My Number 1 course recommendation for self learners (affiliate link): bit.ly/GoogleAnalyticsProfessionalCertificate Udemy Recommendations that I have Personally Taken (affiliate links): ►►Learn Statistics 🤍 ►►Learn Python 🤍 ►►Learn SQL 🤍 ►►Learn Data Analysis (this goes into advanced concepts - learn up to and including Logistic regression - you don't need this before you start applying for jobs but it can help) 🤍 ►►Learn Business Intelligence 🤍 ►►Learn Time Series Analysis (this is an important skill in SOME jobs, but you don't need this before you start applying for jobs) 🤍 For a more technical / hands on approach consider Dataquest (this is where I learned much of what I know). You will learn will learn SQL, Python, R, and more)! This is a recommendation link I do not get paid, but you will get $15 dollars off. app.dataquest.io/referral-signup/qybqz3r8/ ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Recommended Books United States ►► Python for Data Analysis by Wes McKinney 🤍 ►► SQL Cookbook by Anthony Molinaro & Robert de Graff 🤍 UK ►► Python for Data Analysis by Wes McKinney 🤍 ►► SQL Cookbook by Anthony Molinaro & Robert de Graff 🤍 Canada ►►Python for Data Analysis by Wes McKinney 🤍 ►►SQL Cookbook by Anthony Molinaro & Robert de Graff 🤍 These are affiliate links (no extra charge to you, but it helps me out) ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Consider subscribing for weekly tips, tricks, and tutorials. 🤍 Join my Discord Server 🤍 ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Data Link 🤍 Data source fivethirtyeight 🤍 ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ 0:00 Intro 0:20 Data 0:25 Index 0:50 List of Cols 1:00 Set of Cols 1:06 Tuple of Cols 1:28 Less than 3.5 1:41 Performance
In this video, we're going to discuss how to rename the columns of a Python Pandas DataFrame with the help of live examples. So, let's get started. 00:00 Let's Start 02:10 Renaming a Column in DataFrame Using rename() 02:51 Renaming a Column in DataFrame Using rename() Without Creating Another DataFrame 03:26 Renaming a Column in DataFrame By Assigning a List of New Column Names 05:06 Quick Revision of All the Methods with Another Example 07:58 Closing Notes Check Out the Related Articles: How to Rename Columns in Pandas DataFrame [🤍 Complete Pandas Tutorial [🤍 WISH TO CONTRIBUTE VIDEOS ON GEEKSFORGEEKS? Please submit this Google Form - 🤍 Our courses: 🤍 This video is contributed by Akshit Madan. Please Like, Comment, and Share the Video among your friends. #python #pandas #dataframe #datascience #pythonpandas #eda Install our Android App: 🤍 If you wish, translate into the local language and help us reach millions of other geeks: 🤍 Follow us on our Social Media Handles - Twitter- 🤍 LinkedIn- 🤍 Facebook- 🤍 Instagram- 🤍 Reddit- 🤍 Telegram- 🤍 Also, Subscribe if you haven't already! :)
In this short Pandas dataframe tutorial, we will learn six different methods to get the column names from a Pandas dataframe. Knowing how to get column names in Pandas may be very useful as we can use these names to get specific columns by name without having to know which column number (i.e., the index) it is. To get the names of a Pandas dataframe, we can the method columns but also the keys() method. For example, if our dataframe is called df we just type print(df.columns) to get all the columns of the pandas dataframe. » Make sure you subscribe to the channel if you haven't: 🤍 » Code example on how to access the column names: 🤍 » Blog post: 🤍 » Data used 🤍 If you need to know how to read csv files check out this video: 🤍
The next few set of videos will be discussing about Data Analysis using Pandas. This video is about renaming the dataframe column names using the pandas. The dataset used in the demo and the python notebook files can be found in the below Github Repository: 🤍 Connect with me here: LinkedIn: 🤍linkedin.com/in/meenakshi-lakshmanan Subscribe to my channel: 🤍
You will often want to rename the columns of a DataFrame so that their names are descriptive, easy to type, and don't contain any spaces. In this video, I'll demonstrate three different strategies for renaming columns so that you can choose the best strategy to fit your particular situation. SUBSCRIBE to learn data science with Python: 🤍 JOIN the "Data School Insiders" community and receive exclusive rewards: 🤍 RESOURCES GitHub repository for the series: 🤍 "rename" documentation: 🤍 "read_csv" documentation: 🤍 "str.replace" documentation: 🤍 LET'S CONNECT! Newsletter: 🤍 Twitter: 🤍 Facebook: 🤍 LinkedIn: 🤍
The Tutorial helps you to list all the column names in a DataFrame and how to slice only the required columns
Data Science: Python tutorials - In this video you will see how to ADD column names to Pandas DataFrame. Python is an interpreted high-level general-purpose programming language. Its design philosophy emphasizes code readability with its use of significant indentation. Its language constructs as well as its object-oriented approach aim to help programmers write clear, logical code for small and large-scale projects. Pandas is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. It is free software released under the three-clause BSD license. #Python, #Pandas, #PythonTutorials, #Tutorial, #Data, #DataScience, #DataAnalysis, #DataFrame, #ColumnNames
🤍 🤍 Pandas Change Column names - Changing column names within pandas is easy. You only need to decide which method you want to use. Depending on your use case, you can pick the best one for you. The easiest and most popular one will be done via the .rename() method. But look below for 2 other ways. pandas.DataFrame.rename(columns={'old_column_name':'new_column_name'})
How to Change column header names in Python Pandas DataFrames. This Python programming tutorial video shows three different ways to Rename Columns. Code: 🤍 Twitter: 🤍 Subscribe: 🤍 RELATED VIDEOS ► Numpy Intro: 🤍 ► Numpy Intro Jupyter nb: 🤍 ► Pandas Intro: 🤍 ► Pandas Import Data: 🤍 ► Pandas Selecting & Filtering: 🤍 ► Pandas Time Series: 🤍 ► Pandas and MatPlotLib: 🤍 ► Matplotlib Intro: 🤍 #Python #Pandas
Blog post for this video - 🤍 In this video, we will learn how to get the column names of a pandas DataFrame Playlist URL - 🤍 Setup Python Development Environment - 🤍 Introduction to Pandas DataFrame and simple initialization - 🤍 Table of contents - 🤍 Please subscribe, like and share this video #python #pandas #dataframe #dataframe_columns #dev #tutorial #learning #beginners #pythonforbeginners #taming_python
How to change column or row names in Pandas DataFrames with the rename method
This Pandas Tutorial explain How to change the columns names. To Learn More About Pandas , Subscribe to our YouTube Channel: 🤍 Learn Python Online - Enroll Now For a Special Price- Only at Rs 299/ 🤍 Tableau Desktop Certification Training- only at Rs299/ 🤍
String handling Series.str can be used to access the values of the series as strings and apply several methods to it. These can be accessed like Series.str.function/property. Series.str.capitalize() Convert strings in the Series/Index to be capitalized. Series.str.lower() Convert strings in the Series/Index to lowercase. Series.str.title() Convert strings in the Series/Index to titlecase. Series.str.upper() Convert strings in the Series/Index to uppercase. The github link for this video is below 👇👇 🤍
Python pandas tutorial for beginners on how to loop over all the pandas dataframe column name and changing their name to lowercase or uppercase or replacing space with underscore etc. to make them consistent for data analysis. 25+ Recipes to find missing values in python 🤍 India (Instamojo) - 🤍 International (Paypal) - 🤍
how to Change Column Name In Python Pandas Dataframe
How to rename columns in Pandas Dataframe, how to rename rows in the dataframe. Easy simple steps to be followed. For other Videos: 🤍 YouTube 🤍 Kaggle Account: Do follow and comment it helps✌ 🤍 💁♀️💁♀️Website: 🤍 📣🎙🎤Podcast (download and listen while you work, learning made easy with the release of Podcast) 🤍 💁♀️📚Learn at your own pace enroll on Udemy: Get Data Analysis and Visualization Courses on Udemy at a very affordable price. 🚀🚀Designed to help clear your doubts in a more organized and structured manner. Udemy 🤍 😊😊I invite you to join me on Quora and Instagram 🤍 Instagram 🤍 #pythondatavisualization #dataanalysis #pythontutorial #pythonprojects #machinelearning #sourcecode #machinemantra
A Quick way on how to change columns names in a panda Dataframe
python pandas - complete python pandas data science tutorial! In this Python Pandas tutorial, you will learn the various operations of Pandas Groupby function in pandas python: In this tutorial we will learn how to groupby in python pandas and perform aggregate functions Python Pandas Tutorial for Beginners with tutorial and examples on HTML, CSS, JavaScript, XHTML, Java, Python Pandas Tutorial in Hindi Q1 : What is Python pandas used for Get code examples like "python pandas csv" instantly right from your google search results with the Grepper Chrome Extension Dataframes in Python: Introduction to Python Pandas Basics Python Pandas Examples and Solution Concatenate and change the index python pandas if you’ve enjoyed this pandas in python video like us and subscribe to our channel for more similar informative videos and free tutorials. python pandas tutorial | data analysis with python pandas | python training | edureka. in this video we walk through many of the fundamental concepts to use the python pandas data science library. python pandas tutorial | pandas python | intellipaat. work on a real life project on big data analytics using python and gain hands on project experience. introduction to pandas. ►python data science and big data tutorials - .. python has evolved as the most preferred language for data analytics and the increasing search trends on python also indicates that python is the next "big thing" and a must for professionals in the data analytics domain. python runs on windows linux/unix mac os and has been ported to java and . using python makes programmers more productive and their programs ultimately better. this is a short explainer video on pandas in python. in this pandas python tutorial you will learn what is pandas features of pandas pandas vs numpy how to import pandas library what are data structures in pandas data sets in pandas what are data frames and features of data frames and how to create a data frame in pandas in detail. conquer pandas in about 10 minutes! check out the first video i did on pandas:. tutorial on the basics of python's data frames (spread sheet) library pandas in this tutorial. this is the pandas website: .... what is pandas? 2) create dataframe from csv file and python dictionary. got any questions about python panda with source code? pandas intro: . i do some exploratory analysis of the titanic data set and show you how pandas can work with time series using stock market data... Python Pandas Tutorial: Dataframe, Date Range, Slice Groupby in python pandas: Fast Way · python pandas numpy pandas-groupby Python Pandas Tutorial for Beginners In this video we use python pandas & python matplotlib to analyze and answer business questions about 12 months worth of sales data. In this video we walk through many of the fundamental concepts to use the python pandas data science library. Python pandas tutorial (part 1): getting started with data analysis - installation and loading data. Python for data analysis | python pandas tutorial | learn python | python training | edureka. Python pandas tutorial | data analysis with python pandas | python training | edureka. This python pandas tutorial video helps you to learn the following topics:. Learn python pandas dataframe series etc in hindi in one video. Python pandas tutorial 3: different ways of creating dataframe... This python pandas tutorial is taken from the pandas tutorial... Python pandas tutorial | pandas python | intellipaat. Complete python pandas data science tutorial! Python pandas tutorial 2: dataframe basics. Python pandas tutorial in hindi. In this Python Pandas tutorial, you will learn the various operations of Pandas. Python Pandas Tutorial: Dataframe, Date Range, Slice. In python pandas groupby function in pandas python: In this tutorial we will learn how to groupby in python pandas and perform aggregate functions. Groupby function in pandas python: In this tutorial we will learn how to groupby in python pandas and perform aggregate functions. 3 btw) groupby function in pandas python: In this tutorial we will learn how to groupby in python pandas and perform aggregate functions. In this tutorial, we are going to learn about sorting in groupby in Python Pandas library. Groupby in python pandas: Fast Way · python pandas numpy pandas-groupby. Let's explore GroupBy in python pandas with code snippets and examples. I want to improve the time of a groupby in python pandas. Com/pandas-concat/ Course Playlists- Python Pandas Tutorial in Hindi: https://🤍 Python Pandas Tutorial for Beginners with tutorial and examples on HTML, CSS, JavaScript, XHTML, Java,. Python Pandas Tutorial for Beginners: How to Use Pandas for Data Analysis. Welcome to the world of Python Pandas Tutorial for Beginners. Set Header Row, Set Column Names, Set Index Column, Indexing and Slicing, Deleting Columns and Rows, Updating and Adding new Columns and Rows
Data Science: Python tutorials - In this video you will see how to change column names in Pandas DataFrame. Python is an interpreted high-level general-purpose programming language. Its design philosophy emphasizes code readability with its use of significant indentation. Its language constructs as well as its object-oriented approach aim to help programmers write clear, logical code for small and large-scale projects. Pandas is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. It is free software released under the three-clause BSD license. #Python, #Pandas, #PythonTutorials, #Tutorial, #Data, #DataScience, #DataAnalysis, #DataFrame, #Head #Tail
How to View Column Names Python Pandas Dataframe
↓ Code Available Below! ↓ This video shows how to access specific rows of a pandas data frame using the index names of the rows. Data frames don't always have text row names assigned to the columns, but when they do, they can be used to access specific rows instead of using numeric indexing. If you find this video useful, like, share and subscribe to support the channel! ► Subscribe: 🤍 Code used in this Python Code Clip: import pandas as pd import statsmodels.api as sm #(To access mtcars dataset) mtcars = sm.datasets.get_rdataset("mtcars", "datasets", cache=True).data mtcars.head() # Access a row by by name with .loc mtcars.loc["Datsun 710"] # Access multiple rows by by name mtcars.loc[["Datsun 710", "Hornet 4 Drive", "Mazda RX4"]] # Access multiple rows and specific columns by name mtcars.loc[["Datsun 710", "Hornet 4 Drive", "Mazda RX4"], ["mpg","cyl","hp"]] * Note: YouTube does not allow greater than or less than symbols in the text description, so the code above will not be exactly the same as the code shown in the video! I will use Unicode large ＜ and ＞ symbols in place of the standard sized ones. . ⭐ Kite is a free AI-powered coding assistant that integrates with popular editors and IDEs to give you smart code completions and docs while you’re typing. It is a cool application of machine learning that can also help you code faster! Check it out here: 🤍
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Data Science: Python tutorials - In this video you will see how to EXTRACT column names from table (DataFrame) in Python (Pandas). Python is an interpreted high-level general-purpose programming language. Its design philosophy emphasizes code readability with its use of significant indentation. Its language constructs as well as its object-oriented approach aim to help programmers write clear, logical code for small and large-scale projects. Pandas is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. It is free software released under the three-clause BSD license. #Python, #Pandas, #PythonTutorials, #Tutorial, #Data, #DataScience, #DataAnalysis, #DataFrame, #Head #Tail #columns #column #shorts
In this tutorial we will learn about how to work with column names when cleaning a data set in python. Check out the Free Course on- Learn Julia Fundamentals 🤍 Code:🤍 If you liked the video don't forget to leave a like or subscribe. If you need any help just message me in the comments, you never know it might help someone else too. J-Secur1ty JCharisTech Get The Data Science Prime App 🤍 Playstore : 🤍 Need Your Dataset Cleaned check out this gig 🤍 Great Python Books For Mastering Data Science & Machine Learning Python Cookbook:🤍 Python For Data Analysis :🤍 Python Data Science HandBook:🤍 Python Machine Learning by Sebastian Raschka:🤍 Hands On Machine Learning with Scikit-Learn & TensorFlow:🤍 Mastering ML with Scikitlearn:🤍 Monetizing ML:🤍 Building Machine Learning Systems With Python: 🤍 Learn Python The Hard Way,by Zed A. Shaw:🤍 Python Crash Course:Hands on :🤍 Fluent Python:🤍 Follow 🤍 🤍 🤍 🤍
#short #python #pandas #replace #dataframe #rename I want to change the column labels of a Pandas DataFrame from ['$a', '$b', '$c', '$d', '$e'] to ['a', 'b', 'c', 'd', 'e']
Data Science Tips in Python How to rename your column names in pandas dataframes so that you can more quickly and conveniently work with data. This will allow you to use dot notation, which will reduce the number of keystrokes required to access your dataframe columns.
Cleaning up your pandas dataframe headers can be a necessary step to make your dataframes more readable and easier to understand. In this video, I will show you how to clean pandas column headers. See how quickly and easily it is to do so. Your data will be more accessible in no time! 🌎 𝗥𝗘𝗦𝗢𝗨𝗥𝗖𝗘𝗦: Source Code: 🤍 ⭐ 𝗧𝗜𝗠𝗘𝗦𝗧𝗔𝗠𝗣𝗦: 00:00 – Intro 00:14 – Custom Function 01:34 – Dataprep 03:42 – Skimpy 04:13 – Outro ◼️◼️◼️◼️◼️◼️◼️◼️◼️◼️◼️◼️◼️◼️◼️◼️◼️ 𝗖𝗢𝗡𝗡𝗘𝗖𝗧 𝗪𝗜𝗧𝗛 𝗠𝗘: 🌎 Website: 🤍 📝 GitHub: 🤍 ⭐ Discord: 🤍 ▶️ Subscribe: 🤍 🎉 𝗙𝗥𝗘𝗘 𝗘𝘅𝗰𝗲𝗹 𝗔𝗱𝗱-𝗶𝗻 𝘁𝗼 𝗯𝗼𝗼𝘀𝘁 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆 Get it here: 🤍 📚 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗳𝗼𝗿 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗩𝗕𝗔 & 𝗣𝘆𝘁𝗵𝗼𝗻 Check out my recommendations: 🤍 ☕ 𝗕𝘂𝘆 𝗺𝗲 𝗮 𝗰𝗼𝗳𝗳𝗲𝗲❓ If you want to support this channel, you can buy me a coffee here: 🤍
How to concatenate two pandas DataFrames with different columns in the Python programming language. More details: 🤍 Python code of this video: import pandas as pd # Import pandas library in Python data1 = pd.DataFrame({"col1":["a", "b", "c", "d"], # Create first pandas DataFrame "col2":range(4, 0, - 1), "col3":range(11, 15)}) print(data1) # Print first pandas DataFrame data2 = pd.DataFrame({"col1":["x", "y"], # Create second pandas DataFrame "col3":range(3, 1, - 1), "col4":["new", "newest"]}) print(data2) # Print second pandas DataFrame data_concat = pd.concat([data1, data2], # Append two pandas DataFrames ignore_index = True, sort = False) print(data_concat) # Print combined DataFrame Follow me on Social Media: Facebook – Statistics Globe Page: 🤍 Facebook – Group for Discussions & Questions: 🤍 LinkedIn – Statistics Globe Page: 🤍 LinkedIn – Group for Discussions & Questions: 🤍 Twitter: 🤍 Music by bensound.com
How to create a list of column names in the Python programming language. More details: 🤍 Python code of this video: import pandas as pd # Load pandas # Load pandas data = pd.DataFrame({"x1":["xxx", "yyy", "abc", "xxx"], # Create example data "x2":range(1, 5), "x3":["a", "d", "a", "b"], "x4":[10, 30, 50, 70]}) print(data) # Print example data my_column_names_1 = list(data) # Apply list function print(my_column_names_1) # ['x1', 'x2', 'x3', 'x4'] my_column_names_2 = data.columns.tolist() # Apply tolist function print(my_column_names_2) # ['x1', 'x2', 'x3', 'x4'] Follow me on Social Media: Facebook – Statistics Globe Page: 🤍 Facebook – R Programming Group for Discussions & Questions: 🤍 Facebook – Python Programming Group for Discussions & Questions: 🤍 LinkedIn – Statistics Globe Page: 🤍 LinkedIn – R Programming Group for Discussions & Questions: 🤍 LinkedIn – Python Programming Group for Discussions & Questions: 🤍 Twitter: 🤍 Music by bensound.com
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#rename header header_names=['student_name','subj_name','total_marks','grade_id'] file=pd.read_csv("C:\\Users\\home\\Documents\\ytdata2.csv",header=None,names=header_names)
I Create Pandas Dataframe and Check their Columns names with Pandas in 4sec using Python | #python Python pandas is a powerful open-source data manipulation and analysis library that provides easy-to-use data structures and data analysis tools. It is widely used in the field of data science and is built on top of the NumPy library, making it efficient and fast for handling large datasets. With pandas, you can handle various data formats such as CSV, Excel, SQL databases, and more. It offers two primary data structures: Series and DataFrame. A Series is a one-dimensional labeled array that can hold any data type, while a DataFrame is a two-dimensional table with labeled rows and columns, similar to a spreadsheet or SQL table. Python pandas provides a wide range of functionalities for data cleaning, transformation, exploration, and analysis. You can easily load and save data, filter and sort data, merge and join datasets, perform statistical calculations, and handle missing data. Its intuitive syntax and powerful methods make it straightforward to manipulate and analyze data. One of the key features of pandas is its ability to handle missing data gracefully. It provides functions to identify and handle missing values, allowing you to either drop or fill in the missing data based on your requirements. This flexibility makes pandas a valuable tool for data preprocessing tasks. Another notable feature of pandas is its powerful data aggregation and grouping capabilities. You can group data based on specific criteria, apply aggregation functions such as sum, mean, count, etc., and obtain meaningful insights from your datasets. This makes it easier to perform complex data analysis tasks with just a few lines of code. Python pandas also integrates well with other popular data science libraries such as NumPy, Matplotlib, and scikit-learn, allowing you to create comprehensive data analysis and visualization pipelines. In conclusion, Python pandas is an essential library for data manipulation and analysis in Python. Its intuitive and powerful capabilities make it a go-to choice for data scientists and analysts working with tabular data. By leveraging pandas, you can efficiently handle, clean, transform, and analyze datasets, enabling you to gain valuable insights and make informed decisions.
This video shows you how to use the janitor package in R to automatically relabel column titles to make them easy to use and consistant
↓ Code Available Below! ↓ This video shows how to access the columns of a pandas data frame using the numeric index using iloc. Using numeric indexes to get columns can make it easier to select multiple columns or large ranges of columns since you don't have to know or type out all of the column names. If you find this video useful, like, share and subscribe to support the channel! ► Subscribe: 🤍 Code used in this Python Code Clip: import pandas as pd import statsmodels.api as sm #(To access mtcars dataset) mtcars = sm.datasets.get_rdataset("mtcars", "datasets", cache=True).data mtcars.head() # Access a column by numerical index mtcars.iloc[:, 2] # Access multiple column by numerical index mtcars.iloc[:, [2,4,5]] # Access multiple columns and a subset of rows mtcars.iloc[[1,5,7], [2,4,5]] # Access columns with a column subset mtcars[mtcars.columns[[2,4,5]]] * Note: YouTube does not allow greater than or less than symbols in the text description, so the code above will not be exactly the same as the code shown in the video! I will use Unicode large ＜ and ＞ symbols in place of the standard sized ones. . ⭐ Kite is a free AI-powered coding assistant that integrates with popular editors and IDEs to give you smart code completions and docs while you’re typing. It is a cool application of machine learning that can also help you code faster! Check it out here: 🤍
Easy steps explaining how to rename columns in Pandas Dataframe in Python. Visit here for more details: 🤍 Follow us for more articles and updates: 🤍 🤍 🤍
↓ Code Available Below! ↓ This video shows how to access the columns of a pandas data frame using the name of the column. Although base python data structures like lists don't have index names, data frames have named columns that often give information about what is in the column, so it is usually more natural to select columns by name than a numeric index. If you find this video useful, like, share and subscribe to support the channel! ► Subscribe: 🤍 Code used in this Python Code Clip: import pandas as pd import statsmodels.api as sm #(To access mtcars dataset) mtcars = sm.datasets.get_rdataset("mtcars", "datasets", cache=True).data mtcars.head() # Access a column with direct indexing mtcars["mpg"] # Access a column with direct dot indexing mtcars.mpg # Access multiple columns by name mtcars[["mpg","cyl","hp"]] # Access multiple columns by name with a subset of rows by row name mtcars.loc[["Mazda RX4 Wag","Valiant", "Porsche 914-2"],["mpg","cyl","hp"]] # Access multiple columns by name with a subset of rows by row index mtcars.loc[mtcars.index[[2,6,26]],["mpg","cyl","hp"]] * Note: YouTube does not allow greater than or less than symbols in the text description, so the code above will not be exactly the same as the code shown in the video! I will use Unicode large ＜ and ＞ symbols in place of the standard sized ones. . ⭐ Kite is a free AI-powered coding assistant that integrates with popular editors and IDEs to give you smart code completions and docs while you’re typing. It is a cool application of machine learning that can also help you code faster! Check it out here: 🤍
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