Python Pandas Full Course | Learn in 6 hours | Pandas for Data Science and Analysis | Amit Thinks

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Pandas is a powerful and easy-to-use open-source tool built on top of the Python programming language. It is useful for data analysis and manipulation. Python with pandas is widely used in Statistics, Finance, Neuroscience, Economics, Web Analytics, Advertising, etc.

The following lessons are covered in this Pandas course:

Couse Intro: 00:00:00
1. Pandas – Introduction & Features 00:00:51
2. Install & Setup Pandas 00:03:43
3. Create a Pandas DataFrame (Run first program) 00:15:44
4. Pandas DataFrames – Attributes & Methods 00:34:05
5. Join Pandas DataFrame 00:57:45
6. Concatenate Pandas DataFrames 01:03:46
7. Create a Pandas Series 01:11:13
8. Pandas Series – Attributes & Methods 01:25:11
9. Combine two Pandas Series 01:49:08
10. Categorical Data in Pandas 01:56:23
11. Working with Categories in Pandas 02:05:20
12. Read CSV in Pandas 02:11:33
13. Read Excel in Pandas 02:24:28
14. Indexing in Pandas 02:39:06
15. Select multiple columns in Pandas 02:49:59
16. Add a new column in Pandas 03:00:51
17. Delete rows/ columns in Pandas 03:10:50
18. Iterate over rows and columns in Pandas 03:20:28
19. Sorting in Pandas 03:32:09
20. Handle Duplicates in Pandas 03:41:31
21. Clean the Data in Pandas 03:50:51
22. String Operations in Pandas 04:06:02
23. Date Time Operations in Pandas 04:25:02
24. Remove Whitespace or special character in Pandas 04:42:57
25. Group the Data in Pandas 04:53:18
26. Statistical Functions in Pandas 05:12:14
27. Plot a DataFrame in Pandas 05:33:31

#pandastutorial #datascience #amithinks
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The below lessons are explained in this 6 hour Pandas course:

1. Pandas – Introduction & Features 00:00:51
2. Install & Setup Pandas 00:03:43
3. Create a Pandas DataFrame (Run first program) 00:15:44
4. Pandas DataFrames – Attributes & Methods 00:34:05
5. Join Pandas DataFrame 00:57:45
6. Concatenate Pandas DataFrames 01:03:46
7. Create a Pandas Series 01:11:13
8. Pandas Series – Attributes & Methods 01:25:11
9. Combine two Pandas Series 01:49:08
10. Categorical Data in Pandas 01:56:23
11. Working with Categories in Pandas 02:05:20
12. Read CSV in Pandas 02:11:33
13. Read Excel in Pandas 02:24:28
14. Indexing in Pandas 02:39:06
15. Select multiple columns in Pandas 02:49:59
16. Add a new column in Pandas 03:00:51
17. Delete rows/ columns in Pandas 03:10:50
18. Iterate over rows and columns in Pandas 03:20:28
19. Sorting in Pandas 03:32:09
20. Handle Duplicates in Pandas 03:41:31
21. Clean the Data in Pandas 03:50:51
22. String Operations in Pandas 04:06:02
23. Date Time Operations in Pandas 04:25:02
24. Remove Whitespace or special character 04:42:57
25. Group the Data in Pandas 04:53:18
26. Statistical Functions in Pandas 05:12:14
27. Plot a DataFrame in Pandas 05:33:31

Amit.Thinks

Hi Amit, we can use python pandas for ETL Testing Automation(for validations) rite?

mttbpeo

Thank you very much for all the shared and updated information :D

xenovorans

Its showing tuple object is not callable. TypeError even if there's not any error.

print("student record\n", df)
Idk where the error

akanshasharma

First comment
Sir Python for Data science course please making a video

Harshahub

Student1 = {
'Student': ["Ajeet", "Ram", "Ajeet", "Ajay", "Sahil"],
'Rank': [1, 2, 3, 4, 5],
'Marks':[90, 80, 70, 60, 50]
}
ak = pd.DataFrame(Student1)
du = ak.duplicated()
0 False
1 False
2 False
3 False
4 False
dtype: bool
I don't know why all outputs are False

Ajeetkumar-tqvb

itni english aati hoti toa freecode camp se na perh letay

shoaibalam

Please remove subtitles, I am getting irritating

MadhusudhanreddyBapathu

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