# nhp-prep
This is a CLI Tool that has been created to pre-process historical data that has been collected
in multiple instances. This includes data collected at Seneca Zoo and Mellon Institute.
## Requirements
This package **_requires Python 3._**
## Installing
To install this CLI tool you can run the below command
```bash
pip3 install nhp-prep
```
## Updating
If you already have this tool installed, you can update it to the latest stable release by using the following command:
```bash
pip3 install -U nhp-prep
```
Alternatively, you clone this repo and then run this command from **_within_** the repository folder
```bash
python3 setup.py install
```
Another way to install this solution is by running the following command from **_within_** the repository folder:
```bash
pip install -e .
```
Both the above commands would install the package globally and `nhp-prep` will be available on your system.
## How to use
There are multiple instances in which you can use this tool.
```bash
nhp-prep COMMAND [OPTIONS]
```
There are four use-cases (commands) in which you can use this tool:
1. Mapping columns from prior to current format (`reorder-columns`)
```bash
nhp-prep reorder-columns -i <directory_with_files_to_reorder_columns_OR_unique_CSV_file> -o <output_directory> -r <file_with_reference_columns>
```
2. Rename the files to follow current standard (`rename`)
```bash
nhp-prep rename -i <directory_files_to_rename> -o <output_directory>
```
The current format for the file is: `YYYY-MM-DD_HHmmh_<experiment_name>_<Subject_name>_<Researcher_name_or_initials>_data.csv`
3. Timestamp estimation trials from historical data files based on column <X> (`timestamp-estimate`)
```bash
nhp-prep timestamp-estimate -i <directory_with_files_OR_unique_CSV_file> -o <output_directory>
```
### **Since v0.3.0**
Since the previous 3 steps are common across the different datasets collected, the dev team decided to merge them into one single command (`preparation-steps`):
```bash
nhp-prep preparation-steps -i <input_directory> -o <output_directory>
```
**_The previous command will run sequentially the steps 1 to 3. The only command left outside of the bundle is the #4 since that is only applicable for the Baboons' data and requires the additional reference file._**
4. Renaming of Subject according to logs file (needs the file) (`sub-rename`)
```bash
nhp-prep sub-rename -r <file_with_columns_and_reference_subject_names> -i <directory_with_files_OR_unique_CSV_file> -o <output_directory>
```
5. Merge multiple CSV files into a single file. The input should be a directory and so is the output
```bash
nhp-prep merge-csv -i <directory_with_files_OR_unique_CSV_file> -o <output_directory>
```
6. You can perform a data cleaning process by using the merged-csv file from step #5 based on hardcoded rules, such as the name of the Experiment, the Date or the Researcher name as well.
```bash
nhp-prep data-cleaning -i <merged_csv_file> -o <output_directory>
```
## Using the help sub-command
You could also run `nhp-prep --help` to see the available commands and their corresponding usage.
If you want to know all the options available for an specific command, run the following:
```bash
nhp-prep COMMAND --help
```
Example:
```bash
nhp-prep sub-rename --help
```
## Feedback
Please feel free to leave feedback in issues/PRs.
Raw data
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