sqwrl 0.0.1

Sqlachemy Query WRapper Library - pandas-like SQL

<img src=”https://raw.githubusercontent.com/enkratic/sqwrl/master/docs/sqwrl.png” width=”200” height=”200”>

# sqwrl ### Sqlachemy Query WRapper Library

### Quickstart

`python import pandas as pd from sqwrl import DB db = DB('sqlite:///:memory:') df = pd.DataFrame({"x": [1,2,3,4,5], "y": list("abcdf"), "z": [1.0, 1.5, 1.5, 1.2, 1.3]}).set_index("y") ans_df = pd.read_csv("tests/anscombe.csv") db["anscombe"] = ans_df ans_tbl = db["anscombe"] ans_tbl `

Now you can (mostly) use the sqwrl table object as if it were a pandas dataframe!

`python ans_tbl[ans_tbl["dataset"].isin(["I", "II"])][["x", "y"]] `

Use the .df attribute on sqwrl table objects to read their output into pandas DataFrames for any unsupported features.

`python >>> (ans_tbl.df == ans_df).all().all() True `

See [usage](https://nbviewer.jupyter.org/github/enkratic/sqwrl/blob/master/usage.ipynb) for more usage examples.

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### Basic Features:

• [x] Smart Pandas like wheres using getitem

• [x] .loc operations

• [x] Indexing (including reset_index, drops, and appending)

• [x] Sorting

• [x] Most arithmetic operations lazily pushed

• [x] Metadata like length and dtypes

### Advanced Features:

• Groupby - [x] Groupby group iteration - [x] Groupby aggregation - [ ] Groupby aggregation over multiple columns - [ ] Groupby group sizes - [ ] Groupby transform and apply

• Joins - [ ] Pandas-style joins (have the basic framework in place for this)

• Mutation - [ ] Adding, deleting, and editing columns - [ ] Appending existing tables - [ ] Deleting or editing based on conditions