Having set out to build practice plans, for the first week, I had set out the following goals:
- Work on python basics for data analysis
- Intro to Numpy.
- Pandas Basics
What new skills have you learned?
- Numpy is powerful in reference to basic routines for manipulating large arrays and matrices of numeric data.
- Here is the numpy notebook I worked on:
- Generating Random Numbers
- Indexing and selection
- Slicing and operations to manipulate matrices.
- Pandas provides rich data structures and functions designed to make working with structured data fast, easy, and expressive.
- In the pandas notebook, I was able to look at:
- Series and DataFrames
- Multi-Index and Index Hierarchy
- Merging, Joining and Concatenating
- Missing Data, Groupby and aggregate
- Cross Section selection over levels
- I / O operations
What has been easy?
Being conversant with Python, I blazed through the introductions and got to Numpy and Pandas.
Working on data manipulation with Pandas was quite enjoyable and I got to explore lots of functionalities that previously passed me.
What has been difficult?
Running operations a day after learning them was a challenge and constantly had to reference the documentations for help.
How have you used the problem solving strategies to overcome challenges so far?
- Comfortable to work with.
- Generate & manipulate arrays
- Able to import sample datasets from Kaggle and worked some magic.