Tutorial 9- Python Pandas Tutorials In Hindi- Dataframes, Series And Dataframes Operation-Part 1
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- Опубликовано: 20 авг 2024
- Pandas is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. It is free software released under the three-clause BSD license.
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Really thankful to you Krish. I am transitioning my career towards Data field, being with Python experience , your videos helping me a lot to understand these useful concepts. The way you explain is really awesome. This is really a great work you are doing. GBU
indexing assignment to get the col 1 and col 4 we can use these two steps to get the desire outcome
1 df.iloc[:,0::3]
2 df[["Column1","Column4"]]
by using these two steps we can easily get the desire outcome
By the way i really enjoy learning from your videos its very informative and have learned alot
00:22:56 - cream is chessy and question is very easy , answer = df.iloc[0:5,0:4:3] .
pura column hi aa rha hai to rowindex columnindex ki kya jrurt hai sidha hi df[["Column1","Column4"]] kr do
In this code, iloc[:, [0, 3]] selects all rows (:) and the columns at positions 0 and 3 (which correspond to "col1" and "col4"). The resulting DataFrame, selected_columns, will contain only these two columns.
Thanku brother 😊
try this iloc[:,::3]
My Table :
Column1 Column2 Column3 Column4 Column5
Row 1 0 1 2 3 4
Row 2 5 6 7 8 9
Row 3 10 11 12 13 14
Row 4 15 16 17 18 19
Row 5 20 21 22 23 24
Row 6 25 26 27 28 29
Row 7 30 31 32 33 34
Row 8 35 36 37 38 39
Row 9 40 41 42 43 44
Row 10 45 46 47 48 49
1st way : df[['Column1','Column5']]
output :
Column1 Column5
Row 1 0 4
Row 2 5 9
Row 3 10 14
Row 4 15 19
Row 5 20 24
Row 6 25 29
Row 7 30 34
Row 8 35 39
Row 9 40 44
Row 10 45 49
2nd way : df.iloc[:,0:5:4]
output :
Column1 Column5
Row 1 0 4
Row 2 5 9
Row 3 10 14
Row 4 15 19
Row 5 20 24
Row 6 25 29
Row 7 30 34
Row 8 35 39
Row 9 40 44
Row 10 45 49
Respected sir.i have read carefully your present videos..
I hope this video will be very helpful in our kvs examination...
What is kvs exam?
thank you, sir... for this indirect help.
and congrats for your great work.
🙏🙏👍
nice explanation, before I was really confused between these three indexing ways.
Bhai k bolna and dikhna bilkul Qaaleen bhaiya jesa hai :P Respect from Pakistan
Pakistan is now Bhikaristan 😂
Rely thankful krish I'm transforming our career towards data filed it's videos help me going to Data Analytics position.
bro help me plz guide me 🙏
Sb clear kr diya esi hi video search kr rha tha thanks
Thanks, Krish liked the video and the concepts you taught keep doing it
00:01 Introduction to Python Pandas
02:26 Pandas simplifies handling data in Python
06:43 Converting data to a dataframe in Python Pandas
09:13 Creating and viewing dataframes in Python Pandas
14:14 Understanding the indexing and data manipulation techniques in Pandas
16:35 The difference between Dataframes and Series in Pandas
20:28 Understanding the indexing technique using row and column index numbers
22:51 Introduction to basic operations in Pandas
27:46 Using Pandas to perform various data operations
29:48 Understanding unique values in a column.
thank you bhai
I really like the way you teach...
And Thanks your videos are absolutely great .
Hei, bro, you can watch mine too. The playlists for Python and R provide most of the fundamentals. And you can find the link to source files in video description.
@17:04
type(df['column1'])
type(df[['column2','column4']])
in both cases output is dataframe
Superb Video.Thank you so much for making the video..Kindly complete the full python video.
This is useful. Sir ek video matplotlib par bhi
Thankyou so much brother😊💯
Thanks sir , This is very useful.
Thankyou sir
In[ ] : df [[ "column1" , "column4" ]]
Out[ ] : column1 Column4
Row1 0 3
Row2 4 7
Row3 8 11
Row4 12 15
Row5 16 19
Thanks, Krish
thank you bhaiya for your video
you said that kal hii mil jayega iske part 2 and 3. But 2 din hoo geyee, part 2 and part 3 nehi aye 😣
print(data.iloc[0:5,0::3])
Sir, "THANKS A " + "LOT "*3 !!!
By Using index values : df.iloc[:,[0,3]]
By Using loc : df.loc[:,['Column1','Column4']]
Assignment= df.iloc[0:5, 0:4:3]
🤔🤔How?
@@VikasSingh-nq5yx Please watch full video and try to execute :)
@@sanichara_ dekha but 0:4:3 ek sath likh skte hai kya
a=df.iloc[:2,:]
b=df.iloc[3:,:]
pd.concat([a, b], axis=0)
there are two ways to get all those numbers from column1 and column4
In[ ] : df[['column1,'column4]]
and
In[ ] : df.iloc[: , : : 3]
Hi can you please explain the slicing part
Assignment answer is df.iloc[0:,0::3]
What code i would write if i want to sum enrolled number of trainees in my data filtered data class status = complete and contractual trainees class status = cancelled and completed and show it college wise number
Thanks
❤❤
Great bhai ❤❤
Read Column : df[['col1','col4']]
sir name df not defined error kse theek hota anyone please help me with this
Sir mere me type single wale ka pandas.core.frame.Dataframe aa raha hai
Can we skip the row also??
Assignment:
df.iloc[0:,::3]
Column1 Column4
Row1 0 3
Row2 4 7
Row3 8 11
Row4 12 15
Row5 16 19
Hii sir, actually when I started my pandas library and import pandas and try. to create dataframe it show pandas has no attribute of dataframe.. What can I do now??...
Please anyone help me...
@@DeepakSharma-sl5et you need to pass the data as krishan sir passes at starting of the video 0:30
go through that again other wise copy this snippet and try to paste
df = (np.arange(1,20).reshape(5,4),index = ["r1","r2","r3","r4","r5"],columns=["c1","c2","c3","c4"])
Sheet kha milegi
Assigment done by Zeeshan khattak from abdul wali khan university of Mardan pakistan
dp.iloc[:, [0, 3]]
df[["Column1","Column4"]]
df[['Column1','Column4']]
[0:,3:] #answer
df[['Col1' , 'Col4']]
Ans : [:,::3]
noice
How bro? 🤔🤔
df=pd.DataFrame(data=np.arange(0,20).reshape(5,4),index=["Row1","Row2","Row3","Row4","Row5"],columns=["columns1",
"columns2",
"columns3",
"columns4"])
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
Cell In[65], line 1
----> 1 df=pd.DataFrame(data=np.arange(0,20).reshape(5,4),index=["Row1","Row2","Row3","Row4","Row5"],columns=["columns1",
2 "columns2",
3 "columns3",
4 "columns4"])
TypeError: 'numpy.ndarray' object is not callable
df[['colum1','colum5']]
df.iloc [:,1::4]
Correct answer
Can you teach me please double colon :: use?
Start : end : step size
I think .. plz correct me if wrong...
I am learning programming in python
@@mithunmahato309 it's right 👌
@@mithunmahato309 mithun you on Instagram?
df.iloc[:,[0,3]]
Correct ans5
df5.iloc[:,[0,3]]