From 32ff9fdb4fd6cc09e93f7b21f9c1bb9f6a9f6d27 Mon Sep 17 00:00:00 2001
From: zoonalink <zoonalink@gmail.com>
Date: Wed, 28 Dec 2022 23:56:40 +0000
Subject: [PATCH] Task 2- dev report pasted in
---
UFCFVQ-15-M_Programming_Task_2.ipynb | 53 ++++++++++++++++++++++++++--
1 file changed, 51 insertions(+), 2 deletions(-)
diff --git a/UFCFVQ-15-M_Programming_Task_2.ipynb b/UFCFVQ-15-M_Programming_Task_2.ipynb
index d847f7b..edc89ba 100644
--- a/UFCFVQ-15-M_Programming_Task_2.ipynb
+++ b/UFCFVQ-15-M_Programming_Task_2.ipynb
@@ -1773,10 +1773,59 @@
]
},
{
+ "attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
- "add markdown text here"
+ "## Introduction\n",
+ "\n",
+ "The purpose of this report is to reflect on my code development process for Task 2 of the `UFCFQV-15-M Programming_for_Data_Science` coursework.\n",
+ "\n",
+ "## Code Description\n",
+ "\n",
+ "Task_2 requires undertaking a short 'data science' project, making use of Python libraries such as `pandas`, `numpy`, `matplotlib`, `seaborn` and `scipy`. It involves importing two datasets, merging and cleaning data before analysis, including visualisation and appropriate statistical testing. The project is presented in a Jupyter notebook. \n",
+ "\n",
+ "## Development Process\n",
+ "\n",
+ "As with Task_1, my development process roughly followed an iterative CRISP-DM approach. \n",
+ "\n",
+ "Following the import, merge, filter, and clean tasks, I started the analysis. This was very much in the <i>exploratory</i> spirit of Exploratory Data Analysis (EDA). In hindsight, I would like to develop a more structured approach to my EDA.\n",
+ "\n",
+ "Being new to Python, it was a steep learning curve, where I often knew what I wanted to achieve but was not able to do it. I also needed to spend time refreshing my use of statistical tests.\n",
+ "\n",
+ "## Code Evaluation\n",
+ "\n",
+ "The initial tasks (FR7-9) were straight-forward in that it was a case of following the instructions. I did not encounter any problems with these tasks. That said, I always wonder whether there is a <i>more efficient</i> or <i>standard</i> approach. \n",
+ "\n",
+ "I used tools/skills I have encountered so far in terms of Python libraries – especially `pandas`.\n",
+ "\n",
+ "FR10-13 were much more challenging (and interesting) because they are not rigid tasks. Whilst undertaking EDA, I found that I was simultaneously contributing to all four remaining FRs and that I would need to unpick my code for the purposes of the coursework later.\n",
+ "\n",
+ "As a result of significant EDA (mainly visual), I decided to further 'clean' and 'prepare' the data before presenting any visualisations for FR10. I produced a lot of visualisations using both matplotlib and seaborn, experimenting with the many options, occasionally getting lost in the process yet always learning something new.\n",
+ "\n",
+ "I believe that my code is very thorough and shows helpful, relevant output. I made it as readable as possible, commenting where necessary, including adding markdown cells to present the story of the data. \n",
+ "\n",
+ "I would say that I may be presenting too much of similar visualisations - e.g., distributions. This is partly because this is coursework (and the audience is not typical) but also because I am not sure, yet which visualisation is preferable. \n",
+ "\n",
+ "FR11-13 are more succinct as I settled into an approach – style and convention (comments, naming, etc.) but still very thorough - i.e., I investigate using different statistical tests, visualisations and practiced git, markdown, etc.\n",
+ "\n",
+ "### Strengths\n",
+ "\n",
+ "* use of different libraries\n",
+ "* attempt to find a style / approach / format\n",
+ "* thoroughness\n",
+ "* achieving goals\n",
+ "\n",
+ "### Weaknesses\n",
+ "\n",
+ "* too many visualisations\n",
+ "* duplication - i.e. multiple similar visualisations or statistical tests (although in my defence, I want to learn and practice...)\n",
+ "\n",
+ "### Future Improvements\n",
+ "\n",
+ "* learning standards, best practice, efficiencies, more libraries\n",
+ "* balance code / comment / markdown / output\n",
+ "* gain confidence and skills\n"
]
},
{
@@ -1806,7 +1855,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.11.0"
+ "version": "3.11.0 (main, Oct 24 2022, 18:26:48) [MSC v.1933 64 bit (AMD64)]"
},
"vscode": {
"interpreter": {
--
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