Python Pandas extensions for pandas dataframes
# Usage
```
import pandas_ext as px
```
## CSV
By default, pandas will natively read to s3 but won't write to s3.
```
px.read_csv
px.to_csv
```
## Excel
By default, pandas will natively read to s3 but won't write to s3.
To write to xls:
```bash
pip install pandas_ext[xls]
```
To write xlsx:
```bash
pip install pandas_ext[xlsx]
```
## Gdrive
By default, pandas does not read/write to Gdrive.
### For G Suite administrators
At the organization level, one must do the necessary installation and
deployment of the [gdrive lambda service](https://github.com/richiverse/gdrive-lambda/) to get this to work.
You will have to create a service account that shares your G Apps domain with the following APIs enabled:
- Google Drive
- Google Sheets
From there you must download the p12 credentials file and reference it in your settings.yml when deploying the gdrive service.
### For Gdrive clients
Once that is complete, you must share the folder you are interested in reading/writing to the service account email you've received from your administrator.
Locally, for client access you must set the `GDRIVE_URL` and `GDRIVE_KEY` in your projects environment variable in order to talk to
the gdrive lambda service.
```
px.read_gdrive
px.to_gdrive
```
## Parquet
By default, pandas ~does not read/write to Parquet~. This has been added in pandas version 24 and my methods will eventually update to use them but still allow writing to s3.
```
px.read_parquet
px.to_parquet
```
## Spectrum
to_spectrum is unique to pandas_ext.
```
px.to_spectrum
```
## Salesforce
salesforce methods are unique to pandas_ext.
```
px.read_sfdc
px.sfdc_metadata
px.patch_sfdc
px.async_patch_sfdc
```
## SQL service
```
px.read_sql
px.list_backends
## XML
Pandas doesn't natively support writing to XML format.
```
px.to_xml
```
Metadata
Release files for pandas-ext 0.5.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| pandas_ext-0.5.1.tar.gz | 11.7 kB | Without provenance | Details for pandas_ext-0.5.1.tar.gz |
Release files / pandas_ext-0.5.1.tar.gz
| Download URL | pandas_ext-0.5.1.tar.gz |
|---|---|
| Size | 11.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
f5b4659b0bb63242e4184b8e15aff4ca1b6f5b25038a0cefbeb1770a816fe3e9
|
|
BLAKE2b-256 checksum How to use checksums |
307250c7c2aadc3975ebd1ad96173957db4a1b2725d318e3d3b8706fb13b451f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.3
|
Security for pandas-ext 0.5.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.