Timestamps: Introduction: 0:00 Pandas data structure: Series 2:44 Pandas data structure: Series 5:04 Reading in data: 10:01 Inspect The Data: 12:17 Columns and Rows: 15:25 Subsetting Data: 19:00 Casting dtypes: 25:45 Creating new column: 29:00 Adding new Row: 31:19 Plot Examples: 33:05 Save our output: 36:49
Hey I think this is a great tutorial for actual pandas beginners. I have been using pandas for quite some time now, and still learned something. However, an advanced Video would be super great, because I see you doing all sorts of super advanced stuff in your coding videos that blow my mind and that I don't understand! Cheers
Thanks for watching. I’m glad you think it’s a good beginners! I need to think through what I could include for an intermediate/advanced tutorial. My pandas noob video has some good examples/tips if you haven’t already checked that out.
please start a series of ML from scratch like linear regression, logistic regression, decision tree, random forest, k means clustering with python please sir please ..... i m really understanding your teaching style as you teach through hands on
For the last few weeks I've been struggling to learn how to do with Python what I do in 10 minutes with Excel. And a few months ago I spent half a day figuring out most of the steps to do the same analysis in Matlab. Dataframes are ridiculously difficult to deal with I'm learning it because several colleagues said that if I'm looking for a new systems engineering job, I should know Python. Numpy is easy. Pandas dataframes are obscure and clunky.
Interesting to hear you actually find numpy easier to work with than dataframes. I find the opposite because dataframes have an index and column names. It might just take some time and then it will click for you, or maybe you will find something else that works better for your use case. Hope the video was helpful and good luck on your journey.
Hello Rob, Can you help me with this error, please? I can't figure out what i did wrong. Thanks a lot :) df['likeCount'] = pd.to_numeric(df['likeCount'].astype('str')) TypeError: 'Series' object is not callable
@@robmulla Sorry again, I have a question, one more time. What is the best way to work with numbers with decimals, for example, I have a field that has decimal numbers, but I want to convert it to an int.
@@robmulla I truly appreciate the learning content you provide to the masses on your channel. Looking forward to more tutorials on Pandas, liked and subscribed!
What is I have an Excel or csv that has 999 rows but I want to delete 101 thru 999 rows? or Just read the first 100 rows only. Then save that as a new DataFrame as only those 100 rows.
Excellent video, after 2 decades of experience in the software industry I cannot stress more how important it is to have a strong foundation in the basics inorder to attempt something more advanced. Wonderful job
Interesting comment! I have been using python and pandas for years and thought to myself today I should go back and check the basics - so here I am! I find myself still googling every time I have to do simple stuff like change column order or make a copy of a data frame.
Excellent tutorial - Really clear with excellent explanations and concise steps. I've found it useful as a codealonng with a different set of data. Just to get to grasps with Pandas. Thank you!
First pandas or python tutorial I was able to watched more than 10 min of in one sitting. Great job. Looking forward to following you here and on twitch
Dataframe 1 / Table 1 MaterialID |Unit Selling Price |Unit Cost A | 100 | 80 B | 200 | 140 C | 150 | 100 D | 250 | 230 E | 225 | 215 Dataframe 2 / Table 2 Month | Quantity Sold | Material ID Jan | 10 | A Feb | 5 | E Mar | 25 | C Jan | 5 | D Feb | 15 | B Mar | 2 | A Which month highest total sale amount achieved Which month highest profit amount observed Change Quantity Sold from 5 to 7 programatically and find out revised Which month highest total sale amount achieved Which month highest profit amount observed
Hello, I saw one of your post in the youtube forum saying that your Timestamps didn’t worked out properly, I see now that it works. Did you do anything for it to work, any report sent to youtube ? Did the Timestamp worked after you hit the 1000 subscribers or the problem was there before ?
I watched the whole video and I am so amazed at how easy is to do data analysis nowadays. I am the generation that used: Lotus to Excel, due to their limitation we needed to combine Statistical Packages(R, SAS), Graphing(Grapher), and 3D surface mapping (Surffer) plus Visual Basic. Now I have decided to learn Python plus others to go back to some old data for recalibration that was impossible deal with due to memory overloading. Panda is very powerful. Thank you very much for sharing your knowledge.
Glad the video showed you something new. Pandas is a great skill to master and can be really powerful for doing things that aren’t possible to do in excel with large datasets.
I'm not sure, if "thing" is a string it will show as "object" if you count on it it will produce a number integer.. but I'm not sure exactly what you are asking.
@@robmulla hiya - thanks for the reply - at ua-cam.com/video/_Eb0utIRdkw/v-deo.html you can see that the series containing stings has a dtype of object, whereas the series containing the integers has a dtype of int64. I was just wondering why its object and not string?
Thanks for the video, I've learnt a lot! I tried casting different dtypes on the imported Excel spreadsheet columns and found out an interesting issue, when I summed up the numbers in the same column with float64 and int64 dtypes, I got different results (no decimal points involved). Honestly I have no idea why it's working like that! I guess it has to be something with Excel formatting...
Yes! It's actually really easy. Just click the three dots in the top right corner of the kaggle notebook and then click "download code" you then can open it in google colab. You would also need to download and link the data. Why do you prefer colab over a kaggle notebook? They are very similar.
First I want to thank you for sharing your skill and time creating these videos. I thought I was doing pretty well until we got to the Columns and rows section...haha I type the same "set_index" as you did but I kept getting an error. I found out I could run "reset_index", then I did "set_index" again and it worked.
Hi there Rob! I wanna thank you for this fantastic tutorial you made on EDA with Python Pandas library. That really was the most impressive EDA tutorial I've ever watched on YT.
Hi Rob why are addressing Hey u tube ,seems to be quite odd or some sort , mind you U tube is not watching yours Videos we guys are watching our Likes and Views makes your day worth while , So Gentle request be direct to source please address us by " Hi guys " or something .. 🙏🙏🤞Any way Great Videos by You bro. Keep it Up. God Bless You...
Hello Rob, i followed your tutorial and i had an error when you created a new columns. Can you help me with this error. Thank you very much for the great job. /opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead
Hey Carolina. This message usually comes up when you are trying to edit a subset of a previously defined dataframe. The best fix is to add `.copy()` after subsetting and renaming a dataframe. So before you might have: df_small = df.query('thing > 10') Change to: df_small = df.query('thing > 10').copy()
@@robmulla Hey Rob I am getting this error during converting the likecount into integer IntCastingNaNError Traceback (most recent call last) Cell In[126], line 2 1 df['viewCount'].astype('int') ----> 2 df['likeCount'] = df['likeCount'].astype('int').copy()
Timestamps:
Introduction: 0:00
Pandas data structure: Series 2:44
Pandas data structure: Series 5:04
Reading in data: 10:01
Inspect The Data: 12:17
Columns and Rows: 15:25
Subsetting Data: 19:00
Casting dtypes: 25:45
Creating new column: 29:00
Adding new Row: 31:19
Plot Examples: 33:05
Save our output: 36:49
You are awesome @somuSan! Thanks so much for tagging these.
@@robmulla Nah no problem 😅, you are the awesome here, creating such a great end to end tutorial.
I have been using pandas quite a while,learned a lot from your video.
Your presentation was very good to follow through.
Thanks for your hard work.
Thank you!! I never get tired of your videos!!!
I appreciate you watching them!!
absolutely loved this video, one of the best walkthroughs out right now
Hey I think this is a great tutorial for actual pandas beginners. I have been using pandas for quite some time now, and still learned something. However, an advanced Video would be super great, because I see you doing all sorts of super advanced stuff in your coding videos that blow my mind and that I don't understand! Cheers
Thanks for watching. I’m glad you think it’s a good beginners! I need to think through what I could include for an intermediate/advanced tutorial. My pandas noob video has some good examples/tips if you haven’t already checked that out.
@@robmulla Hey thanks :)
No I think I didnt watch it gonna check it out
@@robmulla I checked out the video and yes, I have learned a lot in this one! Also in the timeseries forecasting video. Now I feel like a noob haha
For sure I enjoy this tutorial
Glad you did!
Great video! Interesting way to make a Pandas Introduction. Thank you a lot to share with us your knowlegde!
please start a series of ML from scratch like linear regression, logistic regression, decision tree, random forest, k means clustering with python please sir please ..... i m really understanding your teaching style as you teach through hands on
excellent video! amazing introduction! thank you a lot !
Going on 1 full week of trying to change the font between Jupyter now Kaggle. Idk why I'm obsessed with it
Did you figure it out? Have you watched my tutorial about jupyter/python notebooks?
@@robmulla I have not. Adding it to the que now. Thanks!
Amazing. Thank you!
thumb up. Thumb up
🙏
For the last few weeks I've been struggling to learn how to do with Python what I do in 10 minutes with Excel. And a few months ago I spent half a day figuring out most of the steps to do the same analysis in Matlab. Dataframes are ridiculously difficult to deal with I'm learning it because several colleagues said that if I'm looking for a new systems engineering job, I should know Python. Numpy is easy. Pandas dataframes are obscure and clunky.
Interesting to hear you actually find numpy easier to work with than dataframes. I find the opposite because dataframes have an index and column names. It might just take some time and then it will click for you, or maybe you will find something else that works better for your use case. Hope the video was helpful and good luck on your journey.
Would be helpful to mention Tab kicks off the auto-complete for us n00bs
Good point. Also shift-tab for docstrings!
Hello Rob, Can you help me with this error, please? I can't figure out what i did wrong. Thanks a lot :)
df['likeCount'] = pd.to_numeric(df['likeCount'].astype('str'))
TypeError: 'Series' object is not callable
Strange. Don’t know why it isn’t working. Do you need to set the type to string? Try just dunking to numeric on the column without astype(‘str’)
@@robmulla Sorry again, I have a question, one more time. What is the best way to work with numbers with decimals, for example, I have a field that has decimal numbers, but I want to convert it to an int.
My time stamps still not working -_-
Oh man. I’m sorry. That was really frustrating when it happened to me.
Thank's for everything you share with us
My pleasure! I apprecaite the positive feedback!
At minute 12:40, I believe you meant first "5 rows" and *not* first "5 columns"
Ah! Good catch. Maybe I did it on purpose to make sure you were paying attention 😏
@@robmulla I truly appreciate the learning content you provide to the masses on your channel. Looking forward to more tutorials on Pandas, liked and subscribed!
just getting into DS and kaggleis great the notebook is so easy to use access to datasets is great. thanks for sharing!
Glad it was helpful!
What is I have an Excel or csv that has 999 rows but I want to delete 101 thru 999 rows? or Just read the first 100 rows only. Then save that as a new DataFrame as only those 100 rows.
.head(100) will give you just the first 100 rows.
@@robmulla Thanks for the info
Excellent video, after 2 decades of experience in the software industry I cannot stress more how important it is to have a strong foundation in the basics inorder to attempt something more advanced. Wonderful job
Really appreciate your endorsement! I completely agree about knowing the basics first.
Interesting comment! I have been using python and pandas for years and thought to myself today I should go back and check the basics - so here I am!
I find myself still googling every time I have to do simple stuff like change column order or make a copy of a data frame.
This video deserves to be the most liked Gentle Introduction to Pandas Data Analysis on UA-cam.
Really apprecaite that feedback. Share it with all your friends and maybe we can make it the most liked!
The best video about dataframe, very clear and easy to understand. Thanks Rob👍
Excellent tutorial - Really clear with excellent explanations and concise steps. I've found it useful as a codealonng with a different set of data. Just to get to grasps with Pandas. Thank you!
Awesome! So glad you enjoyed and learned from it.
Hi folks
Does anyone know what keyboard he is using?
Thanks in advance
First pandas or python tutorial I was able to watched more than 10 min of in one sitting. Great job. Looking forward to following you here and on twitch
THank you so much for this video. The quality is amazing and you are such a good teacher.
thank you! greetings from Turkey :)
My pleasure. Glad to know there is someone watching from Turkey!
Have a like good man. Gonna watch all of your videos from 0 ;)
Dataframe 1 / Table 1
MaterialID |Unit Selling Price |Unit Cost
A | 100 | 80
B | 200 | 140
C | 150 | 100
D | 250 | 230
E | 225 | 215
Dataframe 2 / Table 2
Month | Quantity Sold | Material ID
Jan | 10 | A
Feb | 5 | E
Mar | 25 | C
Jan | 5 | D
Feb | 15 | B
Mar | 2 | A
Which month highest total sale amount achieved
Which month highest profit amount observed
Change Quantity Sold from 5 to 7 programatically and find out revised
Which month highest total sale amount achieved
Which month highest profit amount observed
Hello from dom rep next to aiti, how i change the back ground color of kaggle note book .
i cant convert the dtype of likeCount into int64 Can some1 hlp me
Great video
Although I watched this video a long time ago, I wanted to go over a basic explanation. Thanks for sharing your knowledge.
Glad it was helpful!
Your channel is a goldmine ty!
Thanks!
Hello, I saw one of your post in the youtube forum saying that your Timestamps didn’t worked out properly,
I see now that it works.
Did you do anything for it to work, any report sent to youtube ? Did the Timestamp worked after you hit the 1000 subscribers or the problem was there before ?
Hey! Yes. that was really frustrating. I didn't do anything special. It took a few months but then started working. I hope you get it figured out too.
So cool! Pandas for Python makes things so much easier.
Got a new sub here. Thanks for your video.
Thank you so much.
Always welcome!
Great tutorial. Very well explained.
One of the best explanations thank you
I watched the whole video and I am so amazed at how easy is to do data analysis nowadays. I am the generation that used: Lotus to Excel, due to their limitation we needed to combine Statistical Packages(R, SAS), Graphing(Grapher), and 3D surface mapping (Surffer) plus Visual Basic. Now I have decided to learn Python plus others to go back to some old data for recalibration that was impossible deal with due to memory overloading. Panda is very powerful. Thank you very much for sharing your knowledge.
Glad the video showed you something new. Pandas is a great skill to master and can be really powerful for doing things that aren’t possible to do in excel with large datasets.
@@robmulla Yes, you are right. I am learning it and struggling with Jupyter Notebook and Kagle. I like both. I still have a long way to go!
Getting errors while reading csv file
very interesting Tutorial ❤❤
Thank you
You're welcome
I loved this video !!
tysm for this tutorial! :D
Thanks. Easy to follow you.
Great content!!
29:20 - it is giving me value error
Very Nice and Helpful
Thank you for the tutorial!
yass
😉
@@robmulla You just gained a new subscriber✅😊
Wow this was a great video!
Hi - why is the series of 'thing' in mydf dataframe an object dtype, but the 'count' is an int64 dtype? Why is 'thing' not a 'string' dtype?
I'm not sure, if "thing" is a string it will show as "object" if you count on it it will produce a number integer.. but I'm not sure exactly what you are asking.
@@robmulla hiya - thanks for the reply - at ua-cam.com/video/_Eb0utIRdkw/v-deo.html
you can see that the series containing stings has a dtype of object, whereas the series containing the integers has a dtype of int64. I was just wondering why its object and not string?
You're very good at tutorializing.
🙏
Don't use twitch. Will subscribe you here though
Thanks!
That was really good ! Thank you !
Glad you found it helpful. Please share it with anyone else you think might also learn from it!
Thanks for the video, I've learnt a lot! I tried casting different dtypes on the imported Excel spreadsheet columns and found out an interesting issue, when I summed up the numbers in the same column with float64 and int64 dtypes, I got different results (no decimal points involved). Honestly I have no idea why it's working like that! I guess it has to be something with Excel formatting...
21:38
Wow!! I never knew you could use underscores in place of commas for the larger numbers!
Thank you Sir
Amazing video, thank you Rob
Thanks for watching. What with a friend!
How many years have you been doing Data Science?
Thanks for asking. I've been working with data for over 10 years but doing data science specifically for about 6.
What is the shortcut you use @27:16 ???
To copy paste the code while replacing the variable inside?
great
Wow, great video!
Very much enjoyed it.
I will definitely watch your other videos to learn many more techniques.
Thank you.
Really great! I love how you go through step by step and with the end to end examples. Thank you!
Thanks! So well explained.
Glad you enjoyed it!
yes, thanks a lot. l learnt so much. its been interesting and i am going to watch all you videos.
thank you
Thank you for doing the video I learnt a lot about pandas please keep making videos like this.
watching your videos one by one bro, awesome work as usual
Thanks a ton, so glad you are learning from them. Make sure to comment and share so the videos get picked up by the youtube algorithm.
Very helpful! thanks for making this!
Valeu!
Can I use Google Colab to follow along also?
Yes! It's actually really easy. Just click the three dots in the top right corner of the kaggle notebook and then click "download code" you then can open it in google colab. You would also need to download and link the data. Why do you prefer colab over a kaggle notebook? They are very similar.
Thanks nice teaching method you open my mind and eyes
Fantastic video! Thanks much for the lesson.
do you have a discord channel??
Yes I do! Join! discord.gg/KnsDbstv
best I found on YT! underrated video, there should be more likes
You explain these in a very clear way,! Thank u sir 🙏
Awesome information, plainly stated
Thank you very much, an amazing tutorial!!
Hello, What key do you use to open the menus?
Which menu is that? You might want to check out my video on jupyter notebooks when I talk about the keyboard shortcuts I often use.
First I want to thank you for sharing your skill and time creating these videos. I thought I was doing pretty well until we got to the Columns and rows section...haha I type the same "set_index" as you did but I kept getting an error. I found out I could run "reset_index", then I did "set_index" again and it worked.
Very good 🙂👋👋👋👋👋👋😋
Thank you very much
your intro i immediately was like you're my hero!
Love it. Thank you Rob!
Hi there Rob! I wanna thank you for this fantastic tutorial you made on EDA with Python Pandas library. That really was the most impressive EDA tutorial I've ever watched on YT.
Amazing introduction for pandas. This video alone just already covered most of my reporting needs.Thank you
Amazing video!!!
Glad you liked it!!
Good content! 😄
Thanks so much Heitor!
Amazing! Thanks!
Awesome 👍
Thanks Sandra! Glad you liked it.
This video was so useful. Thank you so much!
You're so welcome! Thanks for watching.
this is such a great tutorial, thank you so much!
Glad it was helpful! Please share with others who you think might also learn from it.
Wonderful video - explanation is nice and clean, very intuitive narrative, thank you!
Hi Rob why are addressing Hey u tube ,seems to be quite odd or some sort , mind you U tube is not watching yours Videos we guys are watching our Likes and Views makes your day worth while , So Gentle request be direct to source please address us by " Hi guys " or something .. 🙏🙏🤞Any way Great Videos by You bro. Keep it Up. God Bless You...
Hello Rob, i followed your tutorial and i had an error when you created a new columns. Can you help me with this error. Thank you very much for the great job. /opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
Hey Carolina. This message usually comes up when you are trying to edit a subset of a previously defined dataframe. The best fix is to add `.copy()` after subsetting and renaming a dataframe.
So before you might have:
df_small = df.query('thing > 10')
Change to:
df_small = df.query('thing > 10').copy()
@@robmulla Hey Rob I am getting this error during converting the likecount into integer IntCastingNaNError Traceback (most recent call last)
Cell In[126], line 2
1 df['viewCount'].astype('int')
----> 2 df['likeCount'] = df['likeCount'].astype('int').copy()
Very well explained. easily understood . Didn"t have any issues following along. Good job, brother 😀😀
Glad it helped! I apprecaite the feedback.