| Name | pypdtools JSON |
| Version |
0.0.5
JSON |
| download |
| home_page | |
| Summary | Package with tools for pandas |
| upload_time | 2023-07-14 18:51:03 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.7 |
| license | |
| keywords |
pandas
tools
asyncio
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
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No Travis.
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No coveralls.
|
# Pypdtools
Pypdtools is a Python package that extends the functionality of Pandas DataFrames by introducing the `PtDataFrame` class. `PtDataFrame` provides additional features and enhancements to work with DataFrames in a more convenient and flexible way.
## Features
- Asynchronous iteration support: `PtDataFrame` implements both synchronous and asynchronous iterators, allowing for efficient and convenient data processing in asynchronous contexts.
- Context manager support: `PtDataFrame` can be used as a context manager to easily access the encapsulated Pandas DataFrame.
- Concatenation and reduction: `PtDataFrame` supports concatenation of multiple instances and reduction of a list of `PtDataFrame` objects into a single instance.
- Column extraction: Easily extract a column as a list from a `PtDataFrame`.
**Docs:** <a href="https://msbar.github.io/pypdtools" target="_blank">https://msbar.github.io/pypdtools</a>
**Source code:** <a href="https://github.com/msbar/pypdtools" target="_blank">https://github.com/msbar/pypdtools</a>
## Installation
You can install pypdtools using pip:
```
pip install pypdtools
```
## Usage
Here's an example of how to use the `PtDataFrame` class:
```python
import pandas as pd
from pypdtools.core.dataframe import PtDataFrame
# Create a Pandas DataFrame
data = {
"a": [1, 2, 3],
"b": [4, 5, 6],
"c": [7, 8, 9]
}
df = pd.DataFrame(data)
# Create a PtDataFrame from the Pandas DataFrame
pt_df = PtDataFrame(df)
# Async Iterate over rows
async for row in pt_df:
print(row)
# Concatenate PtDataFrames
pt_df2 = PtDataFrame(df)
concatenated = pt_df + pt_df2
# Reduce a list of PtDataFrames
pt_df3 = PtDataFrame.reduce([pt_df, pt_df2])
# Extract a column as a list
col_values = pt_df.col_to_list("a")
print(col_values)
```
Raw data
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"description": "# Pypdtools\r\n\r\nPypdtools is a Python package that extends the functionality of Pandas DataFrames by introducing the `PtDataFrame` class. `PtDataFrame` provides additional features and enhancements to work with DataFrames in a more convenient and flexible way.\r\n\r\n## Features\r\n\r\n- Asynchronous iteration support: `PtDataFrame` implements both synchronous and asynchronous iterators, allowing for efficient and convenient data processing in asynchronous contexts.\r\n- Context manager support: `PtDataFrame` can be used as a context manager to easily access the encapsulated Pandas DataFrame.\r\n- Concatenation and reduction: `PtDataFrame` supports concatenation of multiple instances and reduction of a list of `PtDataFrame` objects into a single instance.\r\n- Column extraction: Easily extract a column as a list from a `PtDataFrame`.\r\n\r\n**Docs:** <a href=\"https://msbar.github.io/pypdtools\" target=\"_blank\">https://msbar.github.io/pypdtools</a>\r\n\r\n**Source code:** <a href=\"https://github.com/msbar/pypdtools\" target=\"_blank\">https://github.com/msbar/pypdtools</a>\r\n\r\n## Installation\r\n\r\nYou can install pypdtools using pip:\r\n```\r\npip install pypdtools\r\n```\r\n\r\n## Usage\r\n\r\nHere's an example of how to use the `PtDataFrame` class:\r\n\r\n```python\r\nimport pandas as pd\r\nfrom pypdtools.core.dataframe import PtDataFrame\r\n\r\n# Create a Pandas DataFrame\r\ndata = {\r\n \"a\": [1, 2, 3],\r\n \"b\": [4, 5, 6],\r\n \"c\": [7, 8, 9]\r\n}\r\ndf = pd.DataFrame(data)\r\n\r\n# Create a PtDataFrame from the Pandas DataFrame\r\npt_df = PtDataFrame(df)\r\n\r\n# Async Iterate over rows\r\nasync for row in pt_df:\r\n print(row)\r\n\r\n# Concatenate PtDataFrames\r\npt_df2 = PtDataFrame(df)\r\nconcatenated = pt_df + pt_df2\r\n\r\n# Reduce a list of PtDataFrames\r\npt_df3 = PtDataFrame.reduce([pt_df, pt_df2])\r\n\r\n# Extract a column as a list\r\ncol_values = pt_df.col_to_list(\"a\")\r\nprint(col_values)\r\n```\r\n",
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