Saving us time energy and tears on this incredible explanation, thank you once again @Misra :) Really appreciate that you identified and gave us a simple framework to think about Pandas.
Extra Tip: This are different ways of accesing to a df. The df is 3 columns of 'a', 'b', 'c' and 3 rows of 'x', 'y', 'z' import pandas as pd a = { 'a': [1,2,3], 'b': [4,5,6], 'c': [7,8,9],} df = pd.DataFrame(a, index=['x','y','z']) #INDEXING #Row #Column ►►► Format print(df.iloc[0]); print(df.iloc[:,1])# Serie print(df.iloc[[0]]); print(df.iloc[:,[1]])# DataFrame #NAMING #Row #Column ►►► Format print(df.loc['x']); print(df.loc[:,'a']); print(df['a'])# Serie print(df.loc[['x']]); print(df.loc[:,['a']]); print(df[['a']])# DataFrame
Hi, Is there a video on how to export the datasets once it is cleaned and exporting it to overright the existing data, so we can do visualisation through tableau/powerBI on it
There're many functions to save data in different formats. Check the documentation for to_csv, to_excel, to_sql, etc. You can then load those files in other programs.
Thank you for this very useful video!
very well
Saving us time energy and tears on this incredible explanation, thank you once again @Misra :) Really appreciate that you identified and gave us a simple framework to think about Pandas.
Thank you Nathan! I think it's very important to get the basics right before diving deeper as I also try to do in the course as you know. :)
@@misraturp Always on point.
Can we install Jupyter in a website? Or there are a website to work with panda's?
Thank you!
Extra Tip:
This are different ways of accesing to a df.
The df is 3 columns of 'a', 'b', 'c' and 3 rows of 'x', 'y', 'z'
import pandas as pd
a = {
'a': [1,2,3], 'b': [4,5,6], 'c': [7,8,9],}
df = pd.DataFrame(a, index=['x','y','z'])
#INDEXING
#Row #Column ►►► Format
print(df.iloc[0]); print(df.iloc[:,1])# Serie
print(df.iloc[[0]]); print(df.iloc[:,[1]])# DataFrame
#NAMING
#Row #Column ►►► Format
print(df.loc['x']); print(df.loc[:,'a']); print(df['a'])# Serie
print(df.loc[['x']]); print(df.loc[:,['a']]); print(df[['a']])# DataFrame
Thanks for the additional tips!
May I ask how to install pandas?
Thank you!
👉 All you need to know about Pandas in one place! Download my Pandas Cheat Sheet (free) misraturp.gumroad.com/l/pandascs
you are so cute😊😊
cool bro
After NumPy, as a beginner of Pandas, I really like your "detailed" explanation of each lines. Waiting for other parts like this. Thanks^^
Thank you Anıl. I'm happy to hear it was helpful! Next part is coming soon. :)
take respect and love......
Thank you
Great video, Misra!!
Hi, Is there a video on how to export the datasets once it is cleaned and exporting it to overright the existing data, so we can do visualisation through tableau/powerBI on it
There're many functions to save data in different formats. Check the documentation for to_csv, to_excel, to_sql, etc. You can then load those files in other programs.
@@barspinoza cool! ,Thank you 😊