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.
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.
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!
Thank you for this very useful video!
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. :)
very well
Can we install Jupyter in a website? Or there are a website to work with panda's?
Thank you!
May I ask how to install pandas?
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 😊
cool bro
take respect and love......
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😊😊