Hey Lore. In what situations have you had to use a web interactive dashboard at work? And what are the advantages of making your dashboard from scratch rather than use a tool like Tableau?
very good question!! In my case I have worked only with big companies that could afford getting a visualisation tool. the pros of making it all in Python is that it is open source so you dont have to pay a penny. this might be a good use cases for smaller businesses that want to save money on tools... let me know if this makes sense
@@loresowhat That's very helpful👍🏾😊. If I may ask, what is your preferred library, I've heard of streamlit, dash and now Panel, so which would u suggest for beginners?
On your code, while following along I am getting an error: df = df[['Completed Date', 'Description', 'Amount']] #Keeping only desired columns -----> df['Description'] = df['Description'].map(str.lower) #lower case of descriptions TypeError: list indices must be integers or slices, not list I'm not sure how to fix this, as I have tried the apply function as well - any help is appreciated thanks.
The error message you're seeing suggests that df is a list, not a Pandas DataFrame as you're expecting it to be. If you're sure that df should be a DataFrame, then it's possible that you may have accidentally overwritten df with a list earlier in your code. To confirm this, you can check the type of df using the type() function: print(type(df)) If df is a list, you won't be able to use the syntax df['Description'] to access the 'Description' column. Instead, you'll need to use integer indexing, like df[0], to access the first column of the list. If you're still unsure about the cause of the error, you may want to include more of your code or share the complete error message to help me provide a more specific solution.
The code itself is easy to follow, but I'm confused on the use of jupyter notebook. My markdown isn't showing up correctly and nothing seems to be processing for me as it does in your notebook. I've used R shiny to make dashboards and it's much more intuitive in my opinion than anything I've tried to do in python
Great content. By getting the latest month and year individually, you lose the connection between them and will get the highest month number overall, not the latest month. For example, if your data base includes December, 2022, your code will return '12' as `latest_month` and 2023 as `latest_year`. You should get the latest datetime and then get month and year.
@@loresowhat great tutorial! here is the fixed script # Get the latest month in the latest year latest_year = df['Year'].max() last_year_expenses = df[(df['Year'] == latest_year)] latest_month = last_year_expenses['Month'].max() last_month_expenses = df[(df['Month'] == latest_month) & (df['Year'] == latest_year) & (df['Amount'] < 0)] I had to add the last bit because my list of transactions contains positive and negative values
Came here to say the same thing. For anyone looking for an easy method to do this, just grab the max date and then extract the month and year from that.
Hey. Thanks for making this video, it's been really helpful following along with it. Can you please provide the whole dataset that you used in this project as csv ? I made the dataset manually like you mentioned in your code but it seems to be a bit too short for appropriate analysis and studying. So if you could provide the whole dataset , it would be really really helpful. Hope to hear from you soon. Thanks again.
hey that is my bank statement so not really feeling like sharing it online. another solution would be to put the data you have into chatGPT and ask to extend the dataset with dummy data. let me know if that works (you could also do something similar with Python)
Ciao guys, let me know what you think about this project and how to improve it 👍
Sir is there anyway where i can contact or speak with you online as i need some guidance with my Data Analytics career. I am from India
@@satya6693 sure please text me on Instagram at loresowhat 😉
sir can you suggest me some bullet points os suggestion that how there insights we add in resume regarding this project@@loresowhat
This was extremely fun and easy to follow through. Thanks so much for taking the time to make this. New subscriber here!
glad you like it and thanks for the sub!
Thank you so much!! Super well explained
Glad it was helpful!
Hey Lore. In what situations have you had to use a web interactive dashboard at work? And what are the advantages of making your dashboard from scratch rather than use a tool like Tableau?
very good question!! In my case I have worked only with big companies that could afford getting a visualisation tool. the pros of making it all in Python is that it is open source so you dont have to pay a penny. this might be a good use cases for smaller businesses that want to save money on tools... let me know if this makes sense
@@loresowhat That's very helpful👍🏾😊. If I may ask, what is your preferred library, I've heard of streamlit, dash and now Panel, so which would u suggest for beginners?
Hey Lore, nice one :) - please could you specify where to save the images to load into the dashboard?
you can save them in the same folder of the python file
In subsequent videos, please zoom in on your screen so we can easily follow through
will do thanks for the feedback!
On your code, while following along I am getting an error:
df = df[['Completed Date', 'Description', 'Amount']] #Keeping only desired columns
-----> df['Description'] = df['Description'].map(str.lower) #lower case of descriptions
TypeError: list indices must be integers or slices, not list
I'm not sure how to fix this, as I have tried the apply function as well - any help is appreciated thanks.
The error message you're seeing suggests that df is a list, not a Pandas DataFrame as you're expecting it to be.
If you're sure that df should be a DataFrame, then it's possible that you may have accidentally overwritten df with a list earlier in your code. To confirm this, you can check the type of df using the type() function: print(type(df))
If df is a list, you won't be able to use the syntax df['Description'] to access the 'Description' column. Instead, you'll need to use integer indexing, like df[0], to access the first column of the list.
If you're still unsure about the cause of the error, you may want to include more of your code or share the complete error message to help me provide a more specific solution.
wow thanks a lot for the reply, really appreciate your effort and expertise 👍
@@loresowhat Happy to help!!
This is so helpful.
thanks for the comment🙂
I love i love i love ! what a brain!
ahahah thanks 🙂
great video, it would be pretty helpful if you used your mouse to follow along on what code your are explaining. Overall great content
Thanks for the feedback and will definitely keep in mind for the next one 👍
The code itself is easy to follow, but I'm confused on the use of jupyter notebook. My markdown isn't showing up correctly and nothing seems to be processing for me as it does in your notebook. I've used R shiny to make dashboards and it's much more intuitive in my opinion than anything I've tried to do in python
You can replicate the project in R if you feel more comfortable with it 🙂
@@loresowhat So how do we save and add this project to our portfolio?
where we get the project files
link in descriptions
Hey can u make a vedio on the topic ie- How to share the python dashboard, like we share tableau & excel through link.
that's a good tip and will definitely think on how to deliver that 😉
Great content.
By getting the latest month and year individually, you lose the connection between them and will get the highest month number overall, not the latest month.
For example, if your data base includes December, 2022, your code will return '12' as `latest_month` and 2023 as `latest_year`.
You should get the latest datetime and then get month and year.
Good point, thank you so much for your feedback 🙂
@@loresowhat great tutorial!
here is the fixed script
# Get the latest month in the latest year
latest_year = df['Year'].max()
last_year_expenses = df[(df['Year'] == latest_year)]
latest_month = last_year_expenses['Month'].max()
last_month_expenses = df[(df['Month'] == latest_month) & (df['Year'] == latest_year) & (df['Amount'] < 0)]
I had to add the last bit because my list of transactions contains positive and negative values
Came here to say the same thing. For anyone looking for an easy method to do this, just grab the max date and then extract the month and year from that.
@@renrav so what should the code be?? Please provide the code :(
Would deeply appreciate if you could provide the code for what you've suggested.
Do you mean like this: latest_date = df['Date'].max()
Hey. Thanks for making this video, it's been really helpful following along with it. Can you please provide the whole dataset that you used in this project as csv ? I made the dataset manually like you mentioned in your code but it seems to be a bit too short for appropriate analysis and studying. So if you could provide the whole dataset , it would be really really helpful.
Hope to hear from you soon.
Thanks again.
hey that is my bank statement so not really feeling like sharing it online. another solution would be to put the data you have into chatGPT and ask to extend the dataset with dummy data. let me know if that works (you could also do something similar with Python)
@@loresowhat😂