Reading in Files in Pandas | Python Pandas Tutorials

In this series we will be walking through everything you need to know to get started in Pandas! In this video, we learn about Reading in Files in Pandas.

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0:00 Intro
0:58 Read in CSV File
7:39 Read in Txt File
8:53 Read in JSON File
9:32 Read in Excel File
11:30 Looking at Max Rows/Columns
13:35 Looking at Data in DataFrame
18:05 Outro

*All opinions or statements in this video are my own and do not reflect the opinion of the company I work for or have ever worked for*

[christianwiah]

This is how people should teach - easy, smooth, and clear breakdown of concepts.

[bear]

As a python beginner without any programming background, I watched a lot of videos on youtube and found them very hard to follow. This video is the best I've ever watched so far! Thanks!

[damaslan]

Great video from Alex as always. For those who don't know how to access to "copy as a path", you hold shift and right-click the file. I hope this helps.

[victorchinemerem]

Thank you for being a truely outstanding teacher. Your passion for impacting knowledge and your dedication to your students is obvious in everything you do.
I feel so lucky to learn from you sir. I hope you know the priceless impact you are making in so many lives.
Sir, please I have a humble request.
I would appreciate if you would make a video of PYTHON in Data Analysis. A complete series. Much love

[beardedmtbr]

Great video Alex as always, still can’t believe how much I have learned from you and your videos in the last 6 months! Definitely tunning in to brush up and keep it fresh! Bring back the intro!

[vishnuekilwale]

This is the thing I was looking for. I had wish to someone make it more easy.
This is my first step 🚶‍♂️ to learn python.
Lots of love ❤️ for this video

[kpeyialale]

You teach in the most simple way. Thank you for zooming the screen so one can see the text clearly. God bless you. Keep up the good work

[dccoulthard]

Great video. It's been really hard to find good Python videos. It seems like EVERY Python for Data Analytics course that I buy has a teacher that comes from the computer science world, and talks about it that way. Your approach makes is SO much easier for us non-computer scientists to learn!

[litaogechi]

I feel like giving you a hug @Alex. Thanks for relieving me hours searching for this solution. Thanks alot

[kmetriqs]

Thank you Alex! I watched the first video and it automatically switched to the next one, but I came back to hit thumbs-up and leave this comment.
The best Pandas course (I tried many of them)

[theauroralightyr]

Great job, easy to understand. Thank you so much.

[emmanuelojuyenum]

This is so simplified and informative, thanks Alex.

[jueulrr]

The best before the course l was disappointed because I couldn’t open the bath of file and now it’s going up 😂😂❤thanks you’re the best now l will see all your videos and if you have a group not free l will join it really it’s helpful and fantastic explanation!!

[ajaybhandari]

Amazing tutorial.
thanks for straightforwardly explaining this.
I want to request you to please make a video on Mathematics used in Data analysis.

[ivanko-nebo]

not having intro sounded so different. It feels that I've missed some part of the video or even lost a complete previous episode.

[sajuthomas]

Alex, thanks for the video. Nicely explained. Looking forward to future videos.

[chahineatallah]

great video, new for me is the "copy for path" lol, used to do that different way or "type manually"

[DanielKhalil-dh]

🎯 Key points for quick navigation:

00:00:13 *📚 Import the pandas library using the alias 'pd' for convenience in data manipulation.*
00:01:11 *📊 Use `pd.read_csv()` to read CSV files directly into a DataFrame, which allows for easy data manipulation.*
00:02:06 *⚠️ Use a raw string (prefix with 'r') for file paths to avoid Unicode errors caused by backslashes.*
00:03:04 *📝 Pandas offers various parameters for file reading, such as separators and header options, to customize data import.*
00:06:15 *🗂️ Assign the DataFrame to a variable (e.g., df) to retain access to the data for further analysis.*
00:07:37 *📄 Use `read_table()` or specify separators with `read_csv()` to handle tab-separated or text files effectively.*
00:09:13 *🌐 Use `pd.read_json()` to handle JSON files, which often contain semi-structured data.*
00:10:34 *📊 Read Excel files with `pd.read_excel()` and specify sheets using the `sheet_name` parameter if needed.*
00:12:10 *📈 Adjust pandas display options using `pd.set_option()` to view more rows and columns when working with large datasets.*
00:14:46 *🔍 Utilize methods like `df.info()` and `df.head()` to inspect DataFrames for data types and view the first few rows.*

Made with HARPA AI

[Nixsystemd]

Thanks 🙏 Alex, I understood the difference between iloc y loc

[İsmayılSadıqov-vb]

Great video! Thanks, keep moving forward!