First of all thanks to you, I learned ffill, bfill and interpolate functions from here. But it's recommended from many professionals that missing values should be imputed with mean, median & mode.
Could you make a tutorial on Big Data as well, for situations with e.g. 500k rows and 200 columns where you don't see all of your data and don't know what kinds of Nan values to expect and therefore can't name them textually? Big thanks in advance :)
It’s a **kwark called “chunksize=“ the integer passed to it is the amount per chunk. So if you select 1000 and have a df of 500k. It would load 500 times. In pieces
Great tutorial! No need to hesitate on referring to the code snippets btw… I don’t think any sane person watching this has the expectation for you to memorise a to z what you want to articulate…
This video really helped me a lot, but I still got more to understand. I've zero basic knowledge on this. I'm working on a thesis which needs some coding to complete. I've few questions to what you've explained in this video; 1. What if there are lot of dataset and how do you define the missing value for each? 2. What was that in the missing value you defined "np.nan" ? As I said earlier, I'm working on a project which is about human-in-the-loop code. Initially I'll be given the dataset and have to figure out a code to include human for feedback from system (Reinforcement Learning). I would like get your response, and if possible any helpful idea or suggestions on the project mentioned above. Thank you
1. You can use separate lists (with diff variable names,) or a single list as a master list for all the datasets. Depends on the said datasets and the data they contain. 2. np.nan is the "NaN" value in the dataset, which means Not a Number. So basically the np.nan returns a float object whose value is NaN. Hope this helps.
1) u can also use unique function to get only unique values Example df['Customers'].unique in the example above u will get all the unique values in the column 'Customers'
Hi,very nice explanation. I am totally new to python. Can you pls make a tutorial on how to install jupyter and all the other required libraries to perform forecasting.
Please explain to fiilna or replace zero with mean value by groupby... Means you have 3 groups in data frame and you want to fillna with respective to group mean
I have a csv file and when i am using concat function it automatically name unnamed group 1,2,3... Also the alignment gets messy with songle line of code How to fix it
How to get how many type different type of value is there to put in na_values? I mean to say the value you have mentioned for missing_value.. how you are getting that.. we cant check the file if that has huge data
AttributeError Traceback (most recent call last) Cell In[7], line 1 ----> 1 pd_cleaned = pd.dropna() AttributeError: module 'pandas' has no attribute 'dropna i can't find drop na
The dataset which you have is having fewer instances what if we have thousands of rows of data how to find Nan, and Na there in the dataset ...? if you see this please respond ASAP
i have question i wrote print(os.listdir()). but i got many files that is inside my jupyter. may i know how can i import my csv file that i have clean.
Hello sir, thank you so much for the tutorial. I'm actually stuck since my source in a CSV file. Except that sadly the file I'm working is extremely complex with indefinete columns since my main columns are repeated everyday based on the date. I've been stuck on this problem since over a week. Is there a way I could reach out to you and have your mail to maybe help solve this problem? Thanks a lot in advance.
Hii Soumil, right now I'm working on language translation project for that I have collected the data, but I'm facing preprocessing data could you please help me with that.
Sir, by running the data cleaning code in jupyter notebook by following the same code instruction given by u, when i run the code in the output it is not showing unnamed:0 temperature humidity & in my jupyter system it is showing such as v1 &v2 in the output.Why it is so?can u plz explain.
I also faced the same problem. When we creating a new csv file there is no unnamed 0 : column... But if we saved the same file as csv into a folder it will create a new column lke unnamed 0: If we read this data the output will be like in this video.. If repeated each time one extra column will add. For avoiding use index= False while saving a code. It will work
sir, facing a issue in a code to convert the variable from object to integer in jupyter notebook:- it shows the error:-invalid literal for int() with base 10: '-'
Sir, i'm still new in python and this data cleaning thing. And i want to ask what is 11 in df11 ?? is it some kind of function ?? and i also don't understand the snippet concept
First of all thanks to you,
I learned ffill, bfill and interpolate functions from here.
But it's recommended from many professionals that missing values should be imputed with mean, median & mode.
the chill moment when he codes and sips up coffee, cool man great work !!!
Could you make a tutorial on Big Data as well, for situations with e.g. 500k rows and 200 columns where you don't see all of your data and don't know what kinds of Nan values to expect and therefore can't name them textually? Big thanks in advance :)
Up
It’s a **kwark called “chunksize=“ the integer passed to it is the amount per chunk. So if you select 1000 and have a df of 500k. It would load 500 times. In pieces
Bro, you are Doing such great work..
The way you are explaining things is excellent and easy to understand.
Kudos to you .
I just started watching but I see that you are really good man, thanks
Explain the more concepts like standardizing, matching, consolidation so we get all idea about data cleaning.
This
This guy is chill af
This is amazing. I learned a lot. I want to come to India to study Data Analytics
You said everything but but missed the one I am waiting for is filling NaN with mean or media values.
Great tutorial! No need to hesitate on referring to the code snippets btw… I don’t think any sane person watching this has the expectation for you to memorise a to z what you want to articulate…
Thanks Mr. Shah--- I used these commands to prepare a cheat sheet for data cleaning--- regards
thanks for teaching ffill, bfill, interpolate and fillna ...it was a great session
New learned null values like nan, na Nan something new thought us. Thank u...
Nice way of explaining. One request, do make one video on Outlier removal.
Thanks.
you got it !! will add on my to do List
Take the ads off please, thanks, great tutorial by the way.
awesome ,good and precise data cleaning
please load some more stuff related to pandas
This video has really me understand the data cleaning process. Thanks Man.
This video really helped me a lot, but I still got more to understand. I've zero basic knowledge on this. I'm working on a thesis which needs some coding to complete. I've few questions to what you've explained in this video;
1. What if there are lot of dataset and how do you define the missing value for each?
2. What was that in the missing value you defined "np.nan" ?
As I said earlier, I'm working on a project which is about human-in-the-loop code. Initially I'll be given the dataset and have to figure out a code to include human for feedback from system (Reinforcement Learning). I would like get your response, and if possible any helpful idea or suggestions on the project mentioned above.
Thank you
1. You can use separate lists (with diff variable names,) or a single list as a master list for all the datasets. Depends on the said datasets and the data they contain.
2. np.nan is the "NaN" value in the dataset, which means Not a Number. So basically the np.nan returns a float object whose value is NaN.
Hope this helps.
@@debanjangg That was helpful. Thanks mate!🤩
1) u can also use unique function to get only unique values
Example
df['Customers'].unique
in the example above u will get all the unique values in the column 'Customers'
Great job sir . Thank you so much for great explaining . Can u make more videos on data analytics
Learnt something new, THANK YOU!
Thanks a lot bro. The way you explained the steps are really helpful.
Can u tell about yourself... The company u are working and can u give some tips to get a job in data science field as a fresher
Hi,very nice explanation. I am totally new to python. Can you pls make a tutorial on how to install jupyter and all the other required libraries to perform forecasting.
Good and nice explaination
Good job
hats off to you man, you really made my day, you gave me a good confidence today, once again thankyou so much sir
essentially you explained it very well
Great video very helpful
Very useful video keep it up champ
Nice tutorial keep it up
Great job well done n thanx a lot ...I explained v well
Please explain to fiilna or replace zero with mean value by groupby... Means you have 3 groups in data frame and you want to fillna with respective to group mean
I got lost at the very beginning, from the "print(os.listdir())" what i got as my output is very different from what you got
Superb broo Rock on
Thanks Soumil, really helpful !!
Thank you so much. This was really helpful
really great
Thank you for making this video.
BRO YOU SHOULD HAVE UPLOADED CSV FILE AS WELL.
This is a great video😊
So helpful 👌
Thank you sir. I'm very satisfied
Very helpful
please donot stop uploading such videos
good job
Thank you for thr explanation!
I have a csv file and when i am using concat function it automatically name unnamed group 1,2,3... Also the alignment gets messy with songle line of code
How to fix it
thankyou very much soumilshah, its help for me
So please which do you think is more efficient to be used without changing the accuracy of the data
Hi...I have na values but tha boxplot is even not showing it null...
Thank you sir helped me a lot
Sir, please tell me the book from where I can learn all these concepts and programming skills required for this.
Would you be able to provide mentorship. I have started learning DS . Want to keep moving in a direction .jyst don't stop due to coding lag.
well explained .
overall good tutorial, the only thing that is missing is source code (jupyter notebook)
Loved it man
How to do interpolation for categorical variable
how to handle zero values in csv file and how to fill those values
How to get how many type different type of value is there to put in na_values? I mean to say the value you have mentioned for missing_value.. how you are getting that.. we cant check the file if that has huge data
I refer to using mean but thank you it was helpful
AttributeError Traceback (most recent call last)
Cell In[7], line 1
----> 1 pd_cleaned = pd.dropna()
AttributeError: module 'pandas' has no attribute 'dropna
i can't find drop na
what is the use of ffill? Isn't it data corruption? filling nulls with values from above rows
What if the file is not there on which we want to work?
The dataset which you have is having fewer instances
what if we have thousands of rows of data how to find Nan, and Na there in the dataset ...?
if you see this please respond ASAP
Thanks for this video !
what to mention in na_values if we dont know the missing vlaues or there are hundreds of different missing values
i have question i wrote print(os.listdir()). but i got many files that is inside my jupyter. may i know how can i import my csv file that i have clean.
I have to say. "Very Helpful". or print("very helpful") 😂😂
i can use excel for it right ? my work will be more easy kindly persuade me y i have to use python instead of excel here
Hello sir, thank you so much for the tutorial. I'm actually stuck since my source in a CSV file. Except that sadly the file I'm working is extremely complex with indefinete columns since my main columns are repeated everyday based on the date. I've been stuck on this problem since over a week. Is there a way I could reach out to you and have your mail to maybe help solve this problem? Thanks a lot in advance.
Please make a video outlier treatment and detection
5:09 OP
how to cleaning data that is TZAN dataset from kaggle for,music genre classification using cnn?
Hii Soumil, right now I'm working on language translation project for that I have collected the data, but I'm facing preprocessing data could you please help me with that.
How to save the dataset after cleaning process in python?
Use file operations
This was really useful. Thankyou!
Thanks a lot ❤️
How i can handle float values 2.o or 0.04576 kindly let me i am doing a research using a big datasets
here values in missing_values list are case-sensitive or case-insensitive?
Can't we add any value to these NaN?
Pls can you tell me that from where you bought that LAPTOP stand? Pls attach link in comment
why you have used np.nan in the mission_values?
SAME QUESTION.
Hello can you include in this video in cleaning special characters using pandas regular expression?
I need your help please please...how it work in automatically cleaning data?
yo thanks a lot
bro, could you please share the dataset in the description ?
interpolation is basically like average? right?
i want messy dataset for practicing do u know where can i find one? or do u have one ?
Sir, by running the data cleaning code in jupyter notebook by following the same code instruction given by u, when i run the code in the output it is not showing unnamed:0 temperature humidity & in my jupyter system it is showing such as v1 &v2 in the output.Why it is so?can u plz explain.
I also faced the same problem. When we creating
a new csv file there is no unnamed 0 : column... But if we saved the same file as csv into a folder it will create a new column lke unnamed 0:
If we read this data the output will be like in this video.. If repeated each time one extra column will add. For avoiding use index= False while saving a code. It will work
thank you
I want to replace 4wd with fwd in particular column please help
how can we replace using mean, median & mode
sir, facing a issue in a code to convert the variable from object to integer in jupyter notebook:- it shows the error:-invalid literal for int() with base 10: '-'
you can typecast object into int
Sir, i'm still new in python and this data cleaning thing. And i want to ask what is 11 in df11 ?? is it some kind of function ?? and i also don't understand the snippet concept
df11 is just variable you can take anything df11a,df12 df15 anything and snippet is basically a piece of code which he already have
from where i can download this dataset can anyone provide me link
What is noisy data
data.fillna({"P11,":NEGATIVE}) NameError: name 'NEGATIVE' is not defined
?? Please help me ?what can I can do??
Maybe you didn’t install the libraries?
How install Android phone Jupiter notebook
Brother Great video. I need the tea as well. ;)
G real time project need and submitt to clien,