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This video was really helpful and reassuring. I used to get confused about each profession and the difference between their work. Thank you so much!

Loved it mate

Great tutorial but pwd was driving me nuts lol. It's print working directory from Linux.

Your video quality is not don't upload the videos

done the same thing on my channel on power bi for factories attendance records😊

Im so glad this is the first video I watched about data analysis... Actual person doing actual data analysis work... I've learned so much and I am excited and motivated to learn more because of this... Thank you 😊

bro when you're unemployed that avocado toast becomes a luxury 😂

Good day sir, what are some resources that I could use to learn this further?

Awesome video walkthrough! This was practical and easy to follow. I feel like I learned a lot about how I can use Pandas for data analysis. Thanks for putting this together. 🙏

Great video

awesome video

Hatsoff to this tutorial 👏

Can you share a link to the notion block

Please make more sir

I was ready to spend money on a refresher course because I have not used sql in over 10 years. Thank you for this video

thank you for your sharing!

ANYONE SHARE THE LINK TO THE DATASET...? 😅 PLEASE.

Love this video! Very helpful.

Is it still active? Link says no page found

Which skill u need to have to work on data scientists/ Analysts

Sire, you did great but you need to speak slowly & patiently. I'm sure cheesecakes taste better than our own words ;)

Great overview Shashank! I miss your videos. You were one of the first youtubers I watched in the data science field about a year ago and helped motivate me to get my first data analyst role last month. Hope all is well and you come back soon

The first vid was great. The second and third video you lost me. A bunch of copy pasta code and feel to much information was stuffed inside a video. Even as a refresher it’s too much.

Can tha minimal_ds kernel be updated 😭🤣🤣

ahm ahm euhm hmm auh ahm ahm ehm.. Loved your video otherwise, very informal for someone working with excel atm.

Thank you so much for the video

Just stunning! Could you make video about a book "story telling with data" by Cole Nassbaumer Knaflic

Excellent content, it’s helpful

Hey Shashank, great video, it was really helpful. Can you please share the notion link.

I've been looking for this tutorial for a whole week and here i found it !! This vid are recommended for anyone of you that looking for melting the data using pandas!!! I Love it!! Keep it up !

Fake American accent😂😂

Column manipulation starts at 1:20:00

Very Good Video Shashank, now i learned little bit about what actually data analytics is. thanks you.

24:18 erroe { "name": "ImportError", "message": "Missing optional dependency 'openpyxl'. Use pip or conda to install openpyxl.", "stack": "--------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) File c:\\python3.12\\Lib\\site-packages\\pandas\\compat\\_optional.py:135, in import_optional_dependency(name, extra, errors, min_version) 134 try: --> 135 module = importlib.import_module(name) 136 except ImportError: File c:\\python3.12\\Lib\\importlib\\__init__.py:90, in import_module(name, package) 89 level += 1 ---> 90 return _bootstrap._gcd_import(name[level:], package, level) File <frozen importlib._bootstrap>:1387, in _gcd_import(name, package, level) File <frozen importlib._bootstrap>:1360, in _find_and_load(name, import_) File <frozen importlib._bootstrap>:1324, in _find_and_load_unlocked(name, import_) ModuleNotFoundError: No module named 'openpyxl' During handling of the above exception, another exception occurred: ImportError Traceback (most recent call last) Cell In[19], line 1 ----> 1 dataset = pd.read_excel(pwd + \"\\\\Data - Survey Monkey Output Edited.xlsx\") 2 dataset File c:\\python3.12\\Lib\\site-packages\\pandas\\io\\excel\\_base.py:495, in read_excel(io, sheet_name, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, parse_dates, date_parser, date_format, thousands, decimal, comment, skipfooter, storage_options, dtype_backend, engine_kwargs) 493 if not isinstance(io, ExcelFile): 494 should_close = True --> 495 io = ExcelFile( 496 io, 497 storage_options=storage_options, 498 engine=engine, 499 engine_kwargs=engine_kwargs, 500 ) 501 elif engine and engine != io.engine: 502 raise ValueError( 503 \"Engine should not be specified when passing \" 504 \"an ExcelFile - ExcelFile already has the engine set\" 505 ) File c:\\python3.12\\Lib\\site-packages\\pandas\\io\\excel\\_base.py:1567, in ExcelFile.__init__(self, path_or_buffer, engine, storage_options, engine_kwargs) 1564 self.engine = engine 1565 self.storage_options = storage_options -> 1567 self._reader = self._engines[engine]( 1568 self._io, 1569 storage_options=storage_options, 1570 engine_kwargs=engine_kwargs, 1571 ) File c:\\python3.12\\Lib\\site-packages\\pandas\\io\\excel\\_openpyxl.py:552, in OpenpyxlReader.__init__(self, filepath_or_buffer, storage_options, engine_kwargs) 534 @doc(storage_options=_shared_docs[\"storage_options\"]) 535 def __init__( 536 self, (...) 539 engine_kwargs: dict | None = None, 540 ) -> None: 541 \"\"\" 542 Reader using openpyxl engine. 543 (...) 550 Arbitrary keyword arguments passed to excel engine. 551 \"\"\" --> 552 import_optional_dependency(\"openpyxl\") 553 super().__init__( 554 filepath_or_buffer, 555 storage_options=storage_options, 556 engine_kwargs=engine_kwargs, 557 ) File c:\\python3.12\\Lib\\site-packages\\pandas\\compat\\_optional.py:138, in import_optional_dependency(name, extra, errors, min_version) 136 except ImportError: 137 if errors == \"raise\": --> 138 raise ImportError(msg) 139 return None 141 # Handle submodules: if we have submodule, grab parent module from sys.modules ImportError: Missing optional dependency 'openpyxl'. Use pip or conda to install openpyxl." }

Great video! Thank you Shashank. I like your pace and the way you describe how to progress through the tasks. Just btw, my prof for my MSc used to speak way too slowly, so I used to listen to his recordings at 1.25 to 1.50 speed lol (no need to speed you up, its perfect!)

Pro tip guys: use "&" instead of concatenate in excel, does the same thing

I didn't get it when he said "as a data analyst u will spend alot of time trying to get the data to a format u can use" could someone break it down for me + if there is any advice about how to develop this skill

fix your posture

omg I actually done something like this before on Jupyter. I'm a chip designer but we have terabytes of data so we end up doing rudimentary histograms, averaging, filters, organization by different design families. I had to do this stuff twice, one in unix and once in excel because my boss doesn't understand python and wanted to see all the formulas in excel. That was a real freaking pain using excel formulas. This is an eye opener lol. I always assumed data analyst are doing some crazy advanced mathematics and statistics lol

what is this on? pycharm? vs?

24:34

What certifications did u mean??

Great video Shashank! Working on improving your filler phrases "ums" and "uhs" will further improve your viewer retention! Big love!

At 2:12:10, I got some of those unix_time values as negative. What could be the reason? Help

I am stuck at 2:06:24 computer_date = pd.to_datetime(netflix["date_added"]) it's giving me an error called ValueError: time data " August 4, 2017" doesn't match format "%B %d, %Y", at position 218. Please help me.

I wish schools taught these. Not those lame ass basic irrelevant ones.

Thankyou for this. This was Gold.❤

Concatenate is there as a backward compatability because that was the first function they created. Concat is the newer one which can take arrays as arguments. Concatenate cannot accept arrays as arguments, I mean it can but it would spill it over the adjacent cells, as opposed to the newer Concat which would concatenate the strings as expected. In Excel, you can opt to use Power Query for the transformations.

More like this please, i like that it comes from a textbook and also simplified

It is so generous of you to show a real work flow here. A "what DA do daily" vlog isn't help ppl to know nothing, I don't want to see what your lunch is. Your logic is so clear and your skills definitly are sophisticated, I gained a lot from this as a merely beginner. Well done! Many many appreciations.