- Видео 19
- Просмотров 25 928
Data Geek
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Добавлен 6 фев 2023
Welcome to my channel! Here, you'll find tutorials on coding with Python in Jupyter Notebook, data cleaning techniques, and Excel tips-all centered around the world of data. Whether you're a beginner or looking to deepen your skills, join me as we explore practical data solutions and coding tips to boost your data journey!
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Subscribe Today: Tap the subscribe button and turn on notifications to stay ahead with the latest innovations!
Connect With Us: Like, share, and drop your thoughts in the comments-we’d love to hear from you!
Jupyter Notebook Tutorial for Absolute Beginners: Install Anaconda, Shortcuts & Python Basics
Welcome to my channel! In this Jupyter Notebook tutorial for beginners, I’ll show you step-by-step how to install Anaconda and set up Jupyter Notebook for Python programming. This video is perfect for absolute beginners who want to learn Python and understand how to use Jupyter Notebook efficiently.
Download Anaconda: www.anaconda.com/
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Buy Me A Coffee: buymeacoffee.com/datageekismyname
💎Support my channel and hit the Subscribe button 💎
What You'll Learn in This Video:
✅ How to install Anaconda and set up Jupyter Notebook.
✅ Quick introduction to Jupyter Notebooks for beginners.
✅ Basic shortcuts to speed up coding in Jupyter Notebook.
✅ How to write and execute basic ...
Download Anaconda: www.anaconda.com/
*Ways To Support My Channel:*
Buy Me A Coffee: buymeacoffee.com/datageekismyname
💎Support my channel and hit the Subscribe button 💎
What You'll Learn in This Video:
✅ How to install Anaconda and set up Jupyter Notebook.
✅ Quick introduction to Jupyter Notebooks for beginners.
✅ Basic shortcuts to speed up coding in Jupyter Notebook.
✅ How to write and execute basic ...
Просмотров: 130
Видео
Track Real-Time Cryptocurrency Prices Using Python & CoinGecko API | Live Bitcoin & Ethereum Trends
Просмотров 7721 день назад
Learn how to build a real-time cryptocurrency tracker using Python in Jupyter Notebook. This tutorial guides you through fetching live Bitcoin and Ethereum prices with the CoinGecko API, structuring data with Pandas, and visualizing trends with Matplotlib. Perfect for beginners and data enthusiasts, this project showcases dynamic data analysis directly within Jupyter Notebook! DISCLAIMER : This...
Ultimate Data Cleaning Tutorial in Python: Step-by-Step Guide with Jupyter Notebook
Просмотров 32821 день назад
Learn how to clean data efficiently in this Ultimate Data Cleaning Tutorial in Python. This step-by-step guide covers handling missing values, removing duplicates, dealing with outliers, converting data types, and more-all using Jupyter Notebook. Plus, as a bonus, discover how to create simple and effective visualizations to analyze your cleaned data, including bar charts, histograms, and scatt...
How to Automate Web Scraping with Python: Extract Data Using BeautifulSoup and Requests
Просмотров 199Месяц назад
Learn how to automate web scraping tasks using Python in this hands-on tutorial! We’ll show you how to extract data from real websites like Books to Scrape using libraries like BeautifulSoup and Requests. Perfect for beginners looking to dive into web scraping and automate data collection. Watch now to simplify repetitive tasks with Python! #WebScraping #PythonTutorial #BeautifulSoup #DataAutom...
Interactive Dashboard Tutorial: Plotly and Jupyter Notebook for Data Visualization in Python
Просмотров 251Месяц назад
In this tutorial, learn how to create interactive charts and dashboards using Python and Plotly Express in Jupyter Notebook. We'll guide you through building a powerful data visualization dashboard with step-by-step instructions, perfect for anyone interested in Python interactive charts. Whether you're a beginner or looking to enhance your skills, this video covers all you need to know to make...
Predicting Stock Prices with LSTM in Python: 30-Day Forecast Using Yahoo Finance Data.
Просмотров 523Месяц назад
In this tutorial, learn how to predict stock prices with Python using Long Short-Term Memory (LSTM) neural networks. We’ll go through each step-from loading stock data from Yahoo Finance to building and training an LSTM model for a 30-day stock price forecast. Perfect for data science beginners and finance enthusiasts, this video shows how deep learning can be applied to financial predictions. ...
How to Download Anaconda for Jupyter Notebook on Windows 11 | Step-by-Step + Hello World Tutorial
Просмотров 257Месяц назад
In this step-by-step tutorial, I’ll guide you through downloading and installing Anaconda for Jupyter Notebook on Windows 11. Perfect for beginners, this video covers everything from setting up Anaconda to creating your first notebook, renaming it, and running a simple "Hello World" print statement. Get started with Jupyter Notebook in just minutes! *Ways To Support My Channel:* Buy Me A Coffee...
How to Clean Data in Excel: Data Cleaning Tips and Pivot Table Tutorial for Beginners!
Просмотров 1482 месяца назад
In this tutorial, I’ll show you how to clean data in Excel step by step. We’ll cover essential data cleaning techniques like filtering for N/As, removing duplicates, moving columns, and highlighting rows and columns. You’ll also learn how to combine addresses, find and unduplicate by person ID, and create a month and year from dates using simple formulas. Plus, we’ll wrap it up by creating a Pi...
Step-by-Step Data Cleaning in Python with Pandas | Jupyter Notebook Tutorial | CSV to visualization
Просмотров 6 тыс.2 месяца назад
A Step-by-Step Data Cleaning in Python: Removing Duplicates, Nulls & Visualizing Data. Master Data Cleaning with Python Pandas: CSV File to Visualization in Jupyter Notebook. *Ways To Support My Channel:* Buy Me A Coffee: buymeacoffee.com/datageekismyname 💎Support my channel and hit the Subscribe button 💎 In this video, I’ll show you how to clean data using Python, Pandas, and Jupyter Notebook....
How to Identify After-Hours Entries in Excel: Formula Tutorial for Tracking After 5 PM & Weekends
Просмотров 892 месяца назад
In this quick tutorial, I'll show you how to capture after-hours entries in Excel using a simple formula. This method will help you track any activities occurring outside regular business hours (Monday to Friday, 8:00 AM to 5:00 PM) by marking them with a "Y" if they occur after hours. Perfect for Excel users looking to monitor after-hours activities efficiently! Ways To Support My Channel: Buy...
Churn Analysis with Python: Telecom Customer Data | Linear Regression & Multiple Models in Jupyter
Просмотров 2372 месяца назад
In this video, I’ll guide you through a comprehensive analysis of churn data from a telecommunications company. We’ll use Python and Jupyter Notebook to explore key techniques for working with data, including converting categorical to numerical variables, cleaning the dataset, and applying advanced regression models. Ways To Support My Channel: Buy Me A Coffee: buymeacoffee.com/datageekismyname...
Sentiment Analysis with Python: Merge Yelp, IMDb, and Amazon Reviews Using Jupyter Notebook
Просмотров 1083 месяца назад
Ways To Support My Channel: Buy Me A Coffee: buymeacoffee.com/datageekismyname 💎Support my channel and hit the Subscribe button 💎 In this tutorial, I’ll walk you through performing sentiment analysis by merging data from three popular sources: Yelp, IMDb, and Amazon reviews. Using Python and Jupyter Notebook, I'll show you step-by-step how to combine and analyze these datasets to uncover insigh...
Predicting Stock Prices with Machine Learning Using Python Linear Regression Jupyter Notebook
Просмотров 5 тыс.Год назад
In this short video, you will learn how to do a simple step-by-step data analysis of Machine Learning to predict stock prices in Python using Linear Regression. Ways To Support My Channel: Buy Me A Coffee: buymeacoffee.com/datageekismyname 💎Support my channel and hit the Like & Subscribe button 💎 Disclaimer: The material in this video is purely educational and should not be taken as professiona...
Predicting Stock Prices using Regression Analysis with Python Code
Просмотров 9 тыс.Год назад
Predicting Stock Prices using Regression Analysis with Python Code
Reviewing CSV data in python Jupyter Notebook
Просмотров 396Год назад
Reviewing CSV data in python Jupyter Notebook
Uploading CSV file into Python Jupyter Notebook
Просмотров 3,1 тыс.Год назад
Uploading CSV file into Python Jupyter Notebook
The video content is very interesting! I am a little confused: someone sent me a TRC20 USDT and I have the recovery phrase: 「pride pole obtain together second when future mask review nature potato bulb」 How do I extract them?
hi, great video. For better accuracy you can try adding different columns: pct_change would be great. Also you should not use just Open Close High Low, they have very small difference (thats why so correlated)
Thanks so much for sharing.
Give us the data plz
Here is the dataset. I also added it to the description. Have a great day. docs.google.com/spreadsheets/d/1DAJ0NMvM0cPOpmTLHBX8RoqhnCtxhxxk-T8w2hbKqNs/edit?usp=sharing
Good video :) Fun topic I thought about this topic the other day, you went about it in the best way you could. Thanks for the video
Thank you. :-) I am happy you liked it.
Unfortunately this is not correct. The model has a look ahead bias, you are not supposed to know the volume, high and low until the end of the day. So basically you are trying to predict something you already know. This explains why the model has good performances. Don't think that finance is this easy guys
Yes it is not easy! Predicting stock prices is extremely challenging due to the inherent complexity and volatility of financial markets. Stock prices are influenced by a vast array of factors, including company performance, market sentiment, economic indicators, geopolitical events, and even unpredictable phenomena like natural disasters or technological breakthroughs. Moreover, stock prices often reflect collective human behavior, which can be irrational and difficult to model. Even with advanced machine learning algorithms and historical data, the dynamic and often non-linear nature of the market makes it nearly impossible to predict prices with high accuracy consistently. As a result, stock price predictions should always be approached with caution and viewed as estimates rather than certainties.
Thank you ChatGpt
@@lefo4326 No Problem. Thank you for your comment.
Fonts are too small
Thanks for your comment.
Terrible sound. Can`t watch.
Sorry to hear that.
For anyone wanting this code, I put a link in my description of this video to the code. Copy and paste into your Jupyter notebook. Also, I put the dataset used. Save it as a csv file.
❤❤
Soooooooo Sweeeeeeeet ..Data....
Thank you!!! 😁
Wow brief, and on talrget. Please in your next video write code instead of pasting so we code along with you. Excellent
Thanks so much for your advice. I will take it. I appreciate your support.
This is great, can you add timestamps? Id definitely subscribe then
All done. I created timestamps. Thanks for your support.
@@datageekismyname subbed
Thank you. Your video is short, easy to understand, useful and to the point. I thank you for your candid efforts. Please keep up the good work. Cheers!
Thank you so much for your positive feedback. I appreciate it so much.
Great tutorial. But some advice for you: avoid the habit of pasting codes, it's better for the viewer to follow along as you do it, because the main thing is to understand it of the lines mean. Also, the intro sound seems a little harsh. Otherwise thank you for the lessons.
Thank you so much for your input, much appreciated.
Get the dataset and code for FREE. Look in the description. All I ask is to please support my channel and subscribe. Thank you.
You teach Excel very well! Thank you
Thank you! 🙂
can you post a link to your database used
Hey Hi Geekis, I have a one query about ADF pipelines using the tumbling trigger window. When the source file is available, the pipelines succeed. If the file isn't available, the pipeline checks for it, and if it still isn't found, it fails. I download the pipeline status from the last 24 hours into an Excel sheet. Some pipelines have run 200 or 100 times, but I only want to see the last run date and time, not all previous runs. What formula should I use? I’ve tried multiple approaches without success. Could you create a video to help me? Thank you!
Hello, thank you for your comment. For a quick response. Did you try to create a Pivot Table? Insert a Pivot Table with the "Pipeline Name" as the row label. Set the "Run Date" and "Run Time" fields as values and choose "Max" as the aggregation. This will give you a quick view of the last run date and time for each pipeline in your dataset. If this doesn't work. Let me know and I will try and make a video on it.
Hi Geekis, Thanks for your response! I'll do my best to get back to you soon.
@@datageekismyname I tried, but it didn’t work. Could you please give it a try from your side? For your reference, here’s the data: Pipeline Name Run Start Run End Status NRT_2085_PowerAppsTrialSignup_PROD_NRT 10/19/2024, 3:18:00 AM 10/19/2024, 3:19:50 AM Succeeded CustomTransformerOrchestartionStatusFetcher_Prod 10/19/2024, 3:16:10 AM 10/19/2024, 3:18:01 AM Succeeded CustomTransformerOrchestartionStatusFetcher_Prod 10/19/2024, 3:16:05 AM 10/19/2024, 3:17:55 AM Succeeded 1705_PowerAppsFRE_EHToCosmos 10/19/2024, 3:16:01 AM 10/19/2024, 3:18:05 AM Succeeded NRT_BoxPortalEHtoIRISEH_Dynamic 10/19/2024, 3:16:00 AM 10/19/2024, 3:17:59 AM Succeeded CustomTransformerOrchestartionStatusFetcher_Prod 10/19/2024, 3:15:07 AM 10/19/2024, 3:16:07 AM Succeeded NRT_2071_Flow_SB_EH 10/19/2024, 3:15:00 AM 10/19/2024, 3:16:11 AM Succeeded CustomTransformerOrchestartionStatusFetcher_Prod 10/19/2024, 3:14:06 AM 10/19/2024, 3:15:48 AM Succeeded NRT_2017112_BoxPortalEHtoIRISEH_PowerBI 10/19/2024, 3:14:00 AM 10/19/2024, 3:15:52 AM Succeeded CustomTransformerOrchestartionStatusFetcher_Prod 10/19/2024, 3:10:16 AM 10/19/2024, 3:11:35 AM Succeeded CustomTransformerOrchestartionStatusFetcher_Prod 10/19/2024, 3:10:08 AM 10/19/2024, 3:11:47 AM Succeeded 2071_Flow_EH_Cosmos 10/19/2024, 3:10:01 AM 10/19/2024, 3:11:50 AM Succeeded NRT_2071_Flow_SB_EH 10/19/2024, 3:10:00 AM 10/19/2024, 3:11:38 AM Succeeded CustomTransformerOrchestartionStatusFetcher_Prod 10/19/2024, 3:08:05 AM 10/19/2024, 3:09:08 AM Succeeded NRT_1705_PowerApps_SB_EH 10/19/2024, 3:08:00 AM 10/19/2024, 3:09:12 AM Succeeded CustomTransformerOrchestartionStatusFetcher_Prod 10/19/2024, 3:06:32 AM 10/19/2024, 3:08:23 AM Succeeded 1705_PowerAppsFRE_EHToCosmos 10/19/2024, 3:06:00 AM 10/19/2024, 3:08:29 AM Succeeded CustomTransformerOrchestartionStatusFetcher_Prod 10/19/2024, 3:05:07 AM 10/19/2024, 3:06:19 AM Succeeded NRT_2071_Flow_SB_EH 10/19/2024, 3:05:01 AM 10/19/2024, 3:06:23 AM Succeeded MDPBizApps_DRAccountLevel_AllUpMAU_TenantLicenses 10/19/2024, 3:01:07 AM 10/19/2024, 3:19:00 AM Succeeded
formula used in this video: =IF(OR(WEEKDAY(F2)="Y",WEEKDAY(F2)=7),"Y",IF(OR(MOD(F2,1)<8/24,MOD(F2,1)>17/24),"Y","")) ** Please note: replace the "F2" in the formula above with your cell #
I want this code
I put a link in my description of this video to the code. You can copy and paste into your Jupyter notebook.
Very clear. Thank you!
Thank you m this was straight forward
You are very welcome. Thanks so much for watching.
Can you make another video where it predicts let's say 30 days in the future and then plot. Thanks!
Hello, sorry it took a while but I created another video on predictions on 30 days. ruclips.net/video/akDoKV9-1HM/видео.htmlsi=vufjrOQYlqXz64ho
Is there any way one can learn more from you, as a Tutor ? Im on a journey to start a career as developer after recently finishing a Python 6 months program. Going trough the interviews process right now. I like the way you explain things and I would like to steal more knowledge from you if possible, on Data Science and ML/DL.
Sorry I am not doing any tutoring at the moment. I wish you all the luck.
thanks🤍
you are welcome. :-)
Interesting and very easy to understand. Thanks for sharing.
I am happy you liked it. Thank you.
is possible to have the code?
Hello, yes, of course. I put a link in my description of this video to the code. You can copy and paste into your Jupyter notebook.
Is it possible to put a link to the datasets and the code because I find it difficult to write the code from the phone?
Hello. Here is the link to the dataset. Hope this helps. www.kaggle.com/datasets/shreenidhihipparagi/google-stock-prediction
Hello, I put a link in my description of this video to the code. You can copy and paste into your Jupyter notebook.
Please make more videos on similar topic stock prediction/training if possible
Would you please provide me the dataset?
Hello. Here is the link to the dataset. Hope this helps. www.kaggle.com/datasets/shreenidhihipparagi/google-stock-prediction
Amazing. Thank you for what you do. 🙌🏼
Wow! This is great! Thank you.