- Users should be able to get metrics like mean of a single column of a dataset
- Users should be able to extract a few rows that matches a selected criteria.
- Users should be able to be able to treat outliers in a set. That way you can circumvent fake/joke answers and prevent a plot from blowing up.
- Users should be able to be able to treat outliers in a set. That way you can
circumvent fake/joke answers and prevent a plot from blowing up.
#### Plotting
- Users should be able to have different and easy plotting abilities. I would prefer only entering the plot with the columns I need
- Users should be able to have a disribution option so that they see the answers grouped up by size
- Users should be able to have different and easy plotting abilities. I would
prefer only entering the plot with the columns I need
- Users should be able to have a disribution option so that they see
the answers grouped up by size
### User Stories
1. "As a researcher, I want to customize the plotting f.e. like color,axes titles, sorting and colors, so that I can fit the output to my needs"
2. "As a user I want to have detailed documentation/docstrings and logs in case I make a mistake using the code. This should make fixing my mistakes and using the software more straight forward.
3. "As a user I want to know who made contributed to this project and have a proper README and other supporting files.
4. "As a researcher I want the dataset to be properly processed. The data should be cleaned and unnecessary/unusable either already deleted or easyily removable. Thereby the data is easier to understand and work with.
1. "As a researcher, I want to customize the plotting f.e. like color,
axes titles, sorting and colors, so that I can fit the output to my needs"
2. "As a user I want to have detailed documentation/docstrings and logs in
case I make a mistake using the code. This should make fixing my mistakes and
using the software more straight forward.
3. "As a user I want to know who made contributed to this project and have a
proper README and other supporting files.
4. "As a researcher I want the dataset to be properly processed. The data
should be cleaned and unnecessary/unusable either already deleted or easyily
removable. Thereby the data is easier to understand and work with.
5. "As a user I want a license that let me use, view and extend on the code"
6. "As a researcher I want multiple plotting options. I would like
- bar charts,
...
...
@@ -36,7 +45,72 @@
plots to be included.
7. "As a researcher I want easy ways to filter the data and pull information from that. For example
7. "As a researcher I want easy ways to filter the data and pull information
from that. For example
- Pulling the unique answers in one column
- Answers grouped by size
- An option to sort those columns
\ No newline at end of file
- An option to sort those columns
## Non-Functional Requirements
### 1 Performance:
a. The system should be able to handle the chosen dataset efficiently, ensuring
quick response times for data processing and analysis.
b. The system should optimize computational resources to ensure minimal
resource consumption and maximize performance.
### 2 Scalability:
a. The system should support the ability to handle increasing amounts of
data over time without a significant impact on performance.
b. The system should be designed to accommodate future enhancements and
additional functionality seamlessly.
### 3 Reliability:
a. The system should operate without errors and perform as expected under
normal circumstances.
b. The system should handle unexpected inputs, errors, and exceptions
gracefully, providing appropriate error messages or logging mechanisms.
c. The system should implement proper backup and recovery mechanisms to
prevent data loss or corruption.
### 4 Security:
a. The system should ensure the privacy and confidentiality of any introduced
vulnerable data, adhering to applicable data protection laws and regulations.
### 5 Usability:
a. The system should have a concise Jupyter Notebook that is intuitive
and easy to navigate.
b. The system should provide clear instructions and documentation on how to
use and interpret the results.
c. The system should support customization and personalization to accommodate
user preferences.
### 6 Portability:
a. The system should be compatible with multiple operating systems
(e.g., Windows, macOS, Linux) and various web browsers.
b. The system should be designed to facilitate easy deployment and migration
to different environments.
### 7 Interoperability:
a. The system should be compatible with other data science tools, libraries,
and frameworks commonly used in the field.
b. The system should facilitate the exchange and integration of data with other
systems, following standard formats and protocols.
### 8 Documentation:
a. The system should have comprehensive documentation that includes
installation instructions, system architecture, user guides, and developer
guidelines.
b. The documentation should be easily accessible, up-to-date, and regularly
maintained.
### 9 Compliance:
a. The system should adhere to open-source licensing requirements and ensure
that all relevant licenses are appropriately acknowledged and distributed.
b. The system should follow FAIR software development principles to ensure
data findability, accessibility, interoperability, and reusability.
### 10 Performance Monitoring and Logging:
a. The system should implement performance monitoring and logging mechanisms to
track system usage, detect bottlenecks, and identify areas for optimization.
b. The system should log relevant events, errors, and exceptions to facilitate
