>>> import dataiter as di >>> data = di.read_csv("data/listings.csv") >>> data.price_per_guest = data.price / data.guests >>> data.head() . id hood zipcode guests sqft price price_per_guest int64 <U13 <U11 int64 float64 int64 float64 ───── ───────── ─────── ────── ─────── ───── ─────────────── 0 2060 Manhattan 10040 2 nan 100 50.000 1 2595 Manhattan 10018 2 nan 225 112.500 2 3831 Brooklyn 11238 3 500 89 29.667 3 5099 Manhattan 10016 2 nan 200 100.000 4 5121 Brooklyn 11216 2 nan 60 30.000 5 5136 Brooklyn 11232 4 nan 253 63.250 6 5178 Manhattan 10019 2 nan 79 39.500 7 5203 Manhattan 10025 1 nan 79 79.000 8 5238 Manhattan 10002 2 nan 150 75.000 9 5441 Manhattan 10036 2 nan 99 49.500 . >>> data.filter(hood="Manhattan").filter(guests=2).sort(price=1).head() . id hood zipcode guests sqft price price_per_guest int64 <U13 <U11 int64 float64 int64 float64 ──────── ───────── ─────── ────── ─────── ───── ─────────────── 0 42279170 Manhattan 10013 2 nan 0 0.0 1 42384530 Manhattan 10036 2 nan 0 0.0 2 18835820 Manhattan 10021 2 nan 10 5.0 3 20171179 Manhattan 10027 2 nan 10 5.0 4 14858544 Manhattan nan 2 nan 15 7.5 5 31397084 Manhattan 10002 2 nan 19 9.5 6 22289683 Manhattan 10031 2 nan 20 10.0 7 7760204 Manhattan 10040 2 nan 22 11.0 8 43292527 Manhattan 10033 2 nan 22 11.0 9 43268040 Manhattan 10033 2 nan 23 11.5 .
>>> import dataiter as di >>> data = di.read_geojson("data/neighbourhoods.geojson") >>> data.head() . neighbourhood neighbourhood_group geometry <U26 <U13 object ──────────────── ─────────────────── ────────────── 0 Bayswater Queens <MultiPolygon> 1 Allerton Bronx <MultiPolygon> 2 City Island Bronx <MultiPolygon> 3 Ditmars Steinway Queens <MultiPolygon> 4 Ozone Park Queens <MultiPolygon> 5 Fordham Bronx <MultiPolygon> 6 Whitestone Queens <MultiPolygon> 7 Arden Heights Staten Island <MultiPolygon> 8 Arrochar Staten Island <MultiPolygon> 9 Arverne Queens <MultiPolygon> .
>>> import dataiter as di >>> data = di.read_json("data/listings.json") >>> data = data.modify(price_per_guest=lambda x: x.price / x.guests) >>> data.head() [ { "id": 2060, "hood": "Manhattan", "zipcode": "10040", "guests": 2, "sqft": null, "price": 100, "price_per_guest": 50.0 }, { "id": 2595, "hood": "Manhattan", "zipcode": "10018", "guests": 2, "sqft": null, "price": 225, "price_per_guest": 112.5 }, { "id": 3831, "hood": "Brooklyn", "zipcode": "11238", "guests": 3, "sqft": 500.0, "price": 89, "price_per_guest": 29.666666666666668 } ] >>> data.filter(hood="Manhattan").filter(guests=2).sort(price=1).head() [ { "id": 42279170, "hood": "Manhattan", "zipcode": "10013", "guests": 2, "sqft": null, "price": 0, "price_per_guest": 0.0 }, { "id": 42384530, "hood": "Manhattan", "zipcode": "10036", "guests": 2, "sqft": null, "price": 0, "price_per_guest": 0.0 }, { "id": 18835820, "hood": "Manhattan", "zipcode": "10021", "guests": 2, "sqft": null, "price": 10, "price_per_guest": 5.0 } ]