semvec/pypi-packages huggingface dataset:
tidyframe 0.0.3
Clean pandas DataFrame to Tidy DataFrame
License: MIT
Requires Python: !=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*
Keywords: pandas,tidy


Overview
--------------

+ Clean Pandas DataFrame to tidy DataFrame
+ Goal: Help you to create **tidy Pandas Dataframe**
+ Wapper SQLAlchemy function to help you create table, insert table, drop table easily
+ Make tranform nest dictionary easily
+ Make select columns, reorder columns easily
+ Make coalesce columns easily
+ Wapper window function from DataFrame
JsonJ 0.1.6
A library to prase Json Tree data in-order to make things simpler
License: MIT
Keywords: Python 3,Json,Tree,Tree Traversal,Recursive

# JSONJ

JsonJ is a simple Python Library that allows parsing Complicated Nested Json tree to a Simple Json data.
This Library allows converting Complicated Nested Json Data to an Intermediate Simple Json Data, which make it easier to process the original data.

### Example Data Conversion

```sh
########################## FROM #########################################
{"menu": {
  "id": "file",
  "value": "File",
  "popup": {
    "menuitem": [
      {"value": "New", "onclick": "CreateNewDoc()"},
      {"value": "Open", "onclick": "OpenDoc()"},
      {"value": "Close", "onclick": "CloseDoc()"}
    ]
  }
}}

###########################  TO #########################################
{
  'menu': {
   'path': 'menu',
   'isRoot': True,
   'children': ['menu/id', 'menu/value', 'menu/popup']
  },
  'menu/id': {
   'path': 'menu/id',
   'isRoot': False,
   'children': []
  },
            .
            .
            .
  'menu/popup/menuitem/2/value': {
   'path': 'menu/popup/menuitem/2/value',
   'isRoot': False,
   'children': []
  },
  'menu/popup/menuitem/2/onclick': {
   'path': 'menu/popup/menuitem/2/onclick',
   'isRoot': False,
   'children': []
  }
}
```

As you can see, this converted format is Elegant and can be Applied to a Various Task.

### Converted Data Format Description
```sh
            .
            .
            .
'menu/popup/menuitem/2/value': {
   'path': 'menu/popup/menuitem/2/value',
   'isRoot': False,
   'children': []
  },
            .
            .
            .
```

- The key of the data is set to be the path of that particular node from the root Node
- Each Key has a value which in turn is a simple Json with 3 parameters.
  - path: The path of the particular node from the root node (same as that of the key)
  - isRoot: Either it's a Root node or not
  - children: Wheather the particular node has any children or not 

### Installation


```sh
$ pip3 install JsonJ
```

### Usage


```sh
from JsonJ import JsonJ
json = JsonJ(<sample_json_data>)
```
NOTE: PLEASE MAKE SURE THE JSON DATA IS VALID, AS OF NOW THE LIBRARY DOES NOT CHECK WHETHER THE DATA IS VALID OR NOT, BUT THIS VALIDATION WILL BE DONE SOON
### Detailed Usage

```sh
- get_parsed_data() - This function call returns the Intermediate Parsed data
- clean() - This function call clears all the data saved in local variables
```


### Development

Want to contribute? Great!
All you have to do is a Pull Request and start Working

### Todo's

 - Search by node
 - Search by value
 - Json data validator
 - And a lot has to be done

License
----

MIT


**PEACE**
jdict 1.0.0
Dictionary extended with convenience methods that depend heavily on dictionaries being ordered by insertion order.
License: MIT

# jdict

Dictionary extended with convenience methods that depend heavily on dictionaries being ordered by insertion order.

## Requirements

jdict requires Python 3.6+. It will raise an Exception if imported with a lower version.

jdict has no dependencies, except for the following methods which require pandas: `series`, `datarow`, and `datacol`.

## Installation

For now you have to get the source and install with `pip install -e .`

## Usage

```Python
>>> from jdict import jdict
>>> j = jdict(x=3, y=4, z=5)
>>> j.x
3
>>> j.first
('x', 3)
>>> j.first_key
'x'
>>> j.value_list
[3, 4, 5]
>>> j.list
[('x', 3), ('y', 4), ('z', 5)]
>>> j.last
('z', 5)
>>> j.pop_last()
('z', 5)
>>> j
{'x': 3, 'y': 4}
```

and so on. For more about the usage, see the tests.

## Running tests

Run the following commands

1. `pip install pytest` (if you don't have pytest)
2. `pip install pandas` (if you don't have pandas)
3. `pip install -e .` (if you haven't done so already)
4. `pytest`