| S.No | Question |
|---|---|
| *1. | Create a 1D NumPy array with integers from 1 to 5. |
| *2. | Create a 2D NumPy array with shape (3, 3) and initialize it with random numbers. |
| *3. | Find the data type of elements in a given NumPy array. |
| *4. | Find the shape, size, and dimensions of a given NumPy array. |
| *5. | Create a NumPy array with all zeros and a specified shape. |
| *6. | Extract a subset of elements from a NumPy array using indexing and slicing. |
| *7. | Multiply each element of a NumPy array by a scalar value using broadcasting. |
| *8. | Iterate over each element in a NumPy array and calculate its square. |
| *9. | Reshape a 1D NumPy array into a 2D array with shape (2, 3). |
| *10. | Concatenate two NumPy arrays horizontally. |
| S.No | Question |
|---|---|
| #1. | Convert all elements of a NumPy array to uppercase using string functions. |
| #2. | Calculate the mean, median, and standard deviation of a given NumPy array. |
| #3. | Add two NumPy arrays element-wise. |
| #4. | Sort a NumPy array in ascending order. |
| #5. | Find the maximum and minimum values in a given NumPy array. |
| #6. | Count the number of occurrences of a specific value in a NumPy array. |
| #7. | Perform matrix multiplication between two NumPy arrays. |
| #8. | Create a diagonal matrix using NumPy. |
| #9. | Compute the dot product of two vectors using NumPy. |
| #10. | Calculate the determinant of a 2D NumPy array. |
| S.No | Question |
|---|---|
| *1. | Create a pandas Series with integers from 1 to 5. |
| *2. | Create a pandas DataFrame from a dictionary of lists. |
| *3. | Find the shape, size, and dimensions of a given pandas DataFrame. |
| *4. | Access a specific column in a pandas DataFrame. |
| *5. | Calculate the mean, median, and standard deviation of a specific column in a pandas DataFrame. |
| *6. | Apply a custom function to each element in a pandas Series using the apply() function. |
| *7. | Reindex a pandas DataFrame to a specified index. |
| *8. | Iterate over rows of a pandas DataFrame and perform a calculation on a specific column. |
| *9. | Sort a pandas DataFrame by a specific column in ascending order. |
| *10. | Select rows from a pandas DataFrame based on a specific condition. |
| S.No | Question |
|---|---|
| #1. | Perform a count of unique values in a pandas DataFrame column. |
| #2. | Group a pandas DataFrame by a specific column and calculate the sum of another column. |
| #3. | Merge two pandas DataFrames based on a common column. |
| #4. | Perform an inner join between two pandas DataFrames. |
| #5. | Convert a column in a pandas DataFrame to a categorical data type. |
| #6. | Replace missing values in a pandas DataFrame with a specified value. |
| #7. | Drop rows with missing values from a pandas DataFrame. |
| #8. | Calculate the sum of missing values in each column of a pandas DataFrame. |
| #9. | Group a pandas DataFrame by a specific column and fill missing values with the mean of the group. |
| #10. | Perform a left join between two pandas DataFrames. |
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