Very good explanation. You took your time to explain why python will disallow or allow a persons input in certain situations making the viewer learn what to do or not to do. You are a good teacher. That's the kind of videos I truly wanna see and there's it.
Greetings Alex, Your videos are so great and detailed. I have a dataset that has columns for passport number. Some individuals don't have passport leaving the passport number column empty. How do I filter only those without passport number? Thanks😊😊😊
Thanks!! To answer your question: df[df['passport_number'].isna()] will filter down to only rows where the passport number is null (i.e., empty). df[df['passport_number'].notna()] will filter out all passport number null values.
Yes, absolutely. ".loc" is only mandatory if you're filtering on both the rows and the columns. If you're only filtering on the rows, then it is optional.
@@alexsington Thanks, can you make a Playlist on comprehensive data analysis covering all aspects, including REGEX, reading part of pdf files and all libraries pertaining to data analysis such as pandas, Numpy and matplotlib, and seaborn???
I'll definitely be working on a lot of those subjects in the future. Right now, time is my bottleneck. After the holidays, I'll be getting back to work!
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Very good explanation. You took your time to explain why python will disallow or allow a persons input in certain situations making the viewer learn what to do or not to do. You are a good teacher. That's the kind of videos I truly wanna see and there's it.
keep going bro your videos is awsome
I would suggest using pandas query method for these but thanks for the video.
Yeah, that's certainly another way to do it
Greetings Alex,
Your videos are so great and detailed.
I have a dataset that has columns for passport number. Some individuals don't have passport leaving the passport number column empty. How do I filter only those without passport number? Thanks😊😊😊
Thanks!! To answer your question: df[df['passport_number'].isna()] will filter down to only rows where the passport number is null (i.e., empty). df[df['passport_number'].notna()] will filter out all passport number null values.
Can we use 'loc' method as well to filter out rows and columns?
Yes, absolutely. ".loc" is only mandatory if you're filtering on both the rows and the columns. If you're only filtering on the rows, then it is optional.
@@alexsington Thanks, can you make a Playlist on comprehensive data analysis covering all aspects, including REGEX, reading part of pdf files and all libraries pertaining to data analysis such as pandas, Numpy and matplotlib, and seaborn???
I'll definitely be working on a lot of those subjects in the future. Right now, time is my bottleneck. After the holidays, I'll be getting back to work!