مجموعه چیت شیت های کاربردی
1. Python: https://t.co/piKNCap4OM
2. Pandas : https://t.co/khYH8blvbp
3. NumPy: https://t.co/bLQJ7QwpLJ
4. Matplotlib: https://t.co/FetNAcfbNs
5. Seaborn: https://t.co/M5ATDFl74d
6. Scikit-learn? https://t.co/3G7xEehIWC
7. TensorFlow: https://t.co/YEpQ9XO8le
8. Keras: https://t.co/3f4oKzUkkz
9. PyTorch: https://t.co/EwvqWF0gtN
10. SQL: https://t.co/qkePCfAgdD
11. R: https://t.co/BHhM7z6YE5
12. Git: https://t.co/tn4BdsdyJP
13. AWS https://t.co/ZQ1JckpXtM
14. Azure https://t.co/CM3ORVWR9s
15. Google Cloud Platform: https://t.co/q1eRcWJ5kH
16. Dockr : https://t.co/2ncSV6K2gl
17. Kubernetes https://t.co/mjo3mwcR5F
18. Linux Command Line: https://t.co/vKmygIJ68B
19. Jupyter Notebook https://t.co/9Bet0esetC
20. Data Wrangling:https://t.co/0sexNfthZG
21. Data Visualization: https://t.co/hKWpqsTvvt
#cheat_sheet #Python #library
🆔 @Python4all_pro
1. Python: https://t.co/piKNCap4OM
2. Pandas : https://t.co/khYH8blvbp
3. NumPy: https://t.co/bLQJ7QwpLJ
4. Matplotlib: https://t.co/FetNAcfbNs
5. Seaborn: https://t.co/M5ATDFl74d
6. Scikit-learn? https://t.co/3G7xEehIWC
7. TensorFlow: https://t.co/YEpQ9XO8le
8. Keras: https://t.co/3f4oKzUkkz
9. PyTorch: https://t.co/EwvqWF0gtN
10. SQL: https://t.co/qkePCfAgdD
11. R: https://t.co/BHhM7z6YE5
12. Git: https://t.co/tn4BdsdyJP
13. AWS https://t.co/ZQ1JckpXtM
14. Azure https://t.co/CM3ORVWR9s
15. Google Cloud Platform: https://t.co/q1eRcWJ5kH
16. Dockr : https://t.co/2ncSV6K2gl
17. Kubernetes https://t.co/mjo3mwcR5F
18. Linux Command Line: https://t.co/vKmygIJ68B
19. Jupyter Notebook https://t.co/9Bet0esetC
20. Data Wrangling:https://t.co/0sexNfthZG
21. Data Visualization: https://t.co/hKWpqsTvvt
#cheat_sheet #Python #library
🆔 @Python4all_pro
www.pythoncheatsheet.org
Python Cheatsheet
The Python Cheatsheet
#NumPy cheat sheet for #datascience :
*Array Creation*
1.
2.
3.
4.
5.
6.
*Array Operations*
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
*Array Indexing*
ادامه در پست بعد👇
#cheat_sheet #Python
🆔 @Python4all_pro
*Array Creation*
1.
numpy.array()
- Create an array from a list or other iterable.2.
numpy.zeros()
- Create an array filled with zeros.3.
numpy.ones()
- Create an array filled with ones.4.
numpy.empty()
- Create an empty array.5.
numpy.arange()
- Create an array with evenly spaced values.6.
numpy.linspace()
- Create an array with evenly spaced values.*Array Operations*
1.
+
- Element-wise addition.2.
-
- Element-wise subtraction.3.
*
- Element-wise multiplication.4.
/
- Element-wise division.5.
**
- Element-wise exponentiation.6.
numpy.sum()
- Sum of all elements.7.
numpy.mean()
- Mean of all elements.8.
numpy.median()
- Median of all elements.9.
numpy.std()
- Standard deviation.10.
numpy.var()
- Variance.*Array Indexing*
ادامه در پست بعد👇
#cheat_sheet #Python
🆔 @Python4all_pro
#NumPy cheat sheet for #datascience :
*Array Creation*
1.
2.
3.
4.
5.
6.
*Array Operations*
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
*Array Indexing*
1.
2.
3.
*Array Reshaping*
1.
2.
3.
*Array Manipulation*
1.
2.
3.
4.
*Mathematical Functions*
1.
2.
3.
4.
5.
*Statistical Functions*
1.
2.
3.
4.
*Random Number Generation*
1.
2.
3.
*Linear Algebra*
1.
2.
3.
#cheat_sheet #Python
🆔 @Python4all_pro
*Array Creation*
1.
numpy.array()
- Create an array from a list or other iterable.2.
numpy.zeros()
- Create an array filled with zeros.3.
numpy.ones()
- Create an array filled with ones.4.
numpy.empty()
- Create an empty array.5.
numpy.arange()
- Create an array with evenly spaced values.6.
numpy.linspace()
- Create an array with evenly spaced values.*Array Operations*
1.
+
- Element-wise addition.2.
-
- Element-wise subtraction.3.
*
- Element-wise multiplication.4.
/
- Element-wise division.5.
**
- Element-wise exponentiation.6.
numpy.sum()
- Sum of all elements.7.
numpy.mean()
- Mean of all elements.8.
numpy.median()
- Median of all elements.9.
numpy.std()
- Standard deviation.10.
numpy.var()
- Variance.*Array Indexing*
1.
arr[i]
- Access ith element.2.
arr[i:j]
- Access slice from ith to jth element.3.
arr[i:j:k]
- Access slice with step k.*Array Reshaping*
1.
arr.reshape()
- Reshape array.2.
arr.flatten()
- Flatten array.3.
arr.ravel()
- Flatten array.*Array Manipulation*
1.
numpy.concatenate()
- Concatenate arrays.2.
numpy.split()
- Split array.3.
numpy.transpose()
- Transpose array.4.
numpy.flip()
- Flip array.*Mathematical Functions*
1.
numpy.sin()
- Sine.2.
numpy.cos()
- Cosine.3.
numpy.tan()
- Tangent.4.
numpy.exp()
- Exponential.5.
numpy.log()
- Natural logarithm.*Statistical Functions*
1.
numpy.min()
- Minimum value.2.
numpy.max()
- Maximum value.3.
numpy.percentile()
- Percentile.4.
numpy.quantile()
- Quantile.*Random Number Generation*
1.
numpy.random.rand()
- Random numbers.2.
numpy.random.normal()
- Normal distribution.3.
numpy.random.uniform()
- Uniform distribution.*Linear Algebra*
1.
numpy.dot()
- Dot product.2.
numpy.matmul()
- Matrix multiplication.3.
numpy.linalg.inv()
- Matrix inverse.#cheat_sheet #Python
🆔 @Python4all_pro
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