Great vid - although it’s worth mentioning this isn’t going to work if you’ve got a huge table. First from the perspective of running out of ram (loading it in), but then from the 1million row limit in excel on the export
Hi bro, it's very helpful video. Would you illustrate the process when the rows to return (into multiple sheet) are beyond Excel's row limit per sheet?
Excels wrokbook format ".xlsx" has a row limit of 1million. If you data exceeds this threshold the excel would crash or wouldn't simply allow resulting in pandas throwing an exception failing the program. You could export it in ".csv" format since it has no limit. Also to remember er if your data has big numeric values exceeding 8 digits, for example bank account number, use df = df.astype(str) before exporting it to csv or xlsx since excel would conver this number to scientific notation which most of us wouldn't want. Cheers
Hi, If I have about 500 PDFs of financial statements and I want Python to import them and analyze the text readability ( I have seen your video on that topic), how to import the PDFs and understand that they belong to different companies in different years, thanks
What am I missing, since when do you pass arguments with a : instead of = ? What is the Advantage of one over the other? And why is both mixed in this video? For example: pd.read_sql_query(sql: ..., index= ...)
Pretty sure it's supposed to be = in both instances. I'm no Python expert, but all that's passed in to the first argument is the query string. If you know the parameters and pass them in the correct order, you don't need to assign them at all. pd.read_sql_table("data", conn) ^ works without any assignment, per the pandas docs.
@@isaacdruin I didn't think of that. If you're writing an API it makes a lot of sense to do this since those built in export to csv commands copy the result to a file on the file system of the server
Great vid - although it’s worth mentioning this isn’t going to work if you’ve got a huge table. First from the perspective of running out of ram (loading it in), but then from the 1million row limit in excel on the export
That kind of content is awesome and so useful. Do export Excel to SQL Tabels as next please.
@NeuralNine Thanks Brother! I started learning SQL and needed this right now! Cheers!
Hi bro, it's very helpful video. Would you illustrate the process when the rows to return (into multiple sheet) are beyond Excel's row limit per sheet?
Excels wrokbook format ".xlsx" has a row limit of 1million. If you data exceeds this threshold the excel would crash or wouldn't simply allow resulting in pandas throwing an exception failing the program.
You could export it in ".csv" format since it has no limit.
Also to remember er if your data has big numeric values exceeding 8 digits, for example bank account number, use df = df.astype(str) before exporting it to csv or xlsx since excel would conver this number to scientific notation which most of us wouldn't want.
Cheers
Hi, If I have about 500 PDFs of financial statements and I want Python to import them and analyze the text readability ( I have seen your video on that topic), how to import the PDFs and understand that they belong to different companies in different years, thanks
can you help me predict the next series of numbers if i give you the previous 30 numbers by using python and ML? please
What am I missing, since when do you pass arguments with a : instead of = ? What is the Advantage of one over the other? And why is both mixed in this video?
For example: pd.read_sql_query(sql: ..., index= ...)
Pretty sure it's supposed to be = in both instances. I'm no Python expert, but all that's passed in to the first argument is the query string. If you know the parameters and pass them in the correct order, you don't need to assign them at all.
pd.read_sql_table("data", conn)
^ works without any assignment, per the pandas docs.
@@isaacdruin yes thats why i am wondering. He also did the same thing with the insert query when passing the _sql param to cursor.execute()
@@MaxMustermann-on2gd everything outside the quotation marks is likely just being ignored, considering he passes the params in the correct order.
It's not him doing it it's just the stupid pycharm showing him what the provided argument will be used as in the function
@@shaurryabaheti oooooh, i see. I thought he typed it in that way.
Really useful and interesting. thank you!
Thanks!
Thx king!
Why would you want to do this? All sql databases have a way to export tables to csv and it's usually very simple to do
Maybe you're writing an API where the user doesn't have direct access to the database?
@@isaacdruin I didn't think of that. If you're writing an API it makes a lot of sense to do this since those built in export to csv commands copy the result to a file on the file system of the server
Also, believe it or not, a lot of business people really want to have everything as an Excel file.
migrate_to_best_database.mp4