> For the complete documentation index, see [llms.txt](https://developer-mina.gitbook.io/setify/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://developer-mina.gitbook.io/setify/datasets/weather.md). # Weather and Maps ### `temperatures_daily_min()` Daily minimum temperatures in Melbourne, Australia, 1981-1990 {% tabs %} {% tab title="Data" %} ``` date temp 0 1981-01-01 20.7 1 1981-01-02 17.9 2 1981-01-03 18.8 3 1981-01-04 14.6 4 1981-01-05 15.8 ... ... ... 3645 1990-12-27 14.0 3646 1990-12-28 13.6 3647 1990-12-29 13.5 3648 1990-12-30 15.7 3649 1990-12-31 13.0 ``` {% endtab %} {% tab title="Information" %} ``` [3650 rows x 2 columns] RangeIndex: 3650 entries, 0 to 3649 Data columns (total 2 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 date 3650 non-null datetime64[ns] 1 temp 3650 non-null float64 dtypes: datetime64[ns](1), float64(1) memory usage: 57.2 KB None ``` {% endtab %} {% endtabs %} ### `monthly_sunspot()` Sunspots are temporary phenomena on the Sun's photosphere that appear as spots darker than the surrounding areas, This dataset describes a monthly count of the number of observed sunspots for just over 230 years (1749-1983). {% tabs %} {% tab title="Data" %} ``` month sunspot 0 1749-01 58 1 1749-02 62.6 2 1749-03 70 3 1749-04 55.7 4 1749-05 85 ... ... ... 2815 1983-08 71.8 2816 1983-09 50.3 2817 1983-10 55.8 2818 1983-11 33.3 2819 1983-12 33.4 ``` {% endtab %} {% tab title="Information" %} ``` [2820 rows x 2 columns] Int64Index: 2820 entries, 0 to 2819 Data columns (total 2 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 month 2820 non-null object 1 sunspot 2820 non-null float64 dtypes: float64(1), object(1) memory usage: 66.1+ KB ``` {% endtab %} {% endtabs %} ### `walmart_store_location()` Walmart Inc. multinational retail corporation that operates a chain of hypermarkets, department stores, and grocery stores, headquartered in Bentonville, Arkansas. The company was founded by Sam Walton in 1962. This is a complete list of all Walmart store locations, along with their geographic coordinates, Street addresses, City, State, ZIP code, etc in the US. [Source](https://data.world/data-hut/walmart-store-location-data) {% tabs %} {% tab title="Data" %} ``` city country latitude longitude name ... phone_number_1 state street_address url zip_code 0 Conway US 35.1087 -92.4369 Conway Supercenter ... 501-329-0023 AR 1155 Hwy 65 North https://www.walmart.com/store/5/conway-ar/details 72032 1 Sikeston US 36.8574 -89.5861 Sikeston Supercenter ... 573-472-3020 MO 1303 S Main St https://www.walmart.com/store/9/sikeston-mo/de... 63801 2 Tahlequah US 35.8888 -94.9799 Tahlequah Supercenter ... 918-456-8804 OK 2020 S Muskogee Ave https://www.walmart.com/store/10/tahlequah-ok/... 74464 3 Mountain Home US 36.355 -92.341 Mountain Home Supercenter ... 870-492-9299 AR 65 Wal Mart Dr https://www.walmart.com/store/11/mountain-home... 72653 4 Claremore US 36.294 -95.6271 Claremore Supercenter ... 918-341-2765 OK 1500 S Lynn Riggs Blvd https://www.walmart.com/store/12/claremore-ok/... 74017 ... ... ... ... ... ... ... ... ... ... ... ... 4649 Pearland US 29.5564 -95.4158 Pearland Neighborhood Market ... 713-570-7925 TX 12631 Broadway Street https://www.walmart.com/store/7361/pearland-tx... 77584 4650 Bentonville US 36.3575 -94.2147 Bentonville Gas Station ... 479-271-2209 AR 1300 S Walton Blvd https://www.walmart.com/store/7368/bentonville... 72712 4651 Millcreek US 40.691 -111.847 Millcreek Pickup only ... 801-467-2882 UT 3701 S Highland Dr https://www.walmart.com/store/8855/millcreek-u... 84106 4652 Dallas US 32.9634 -96.7703 Dallas Supercenter ... 972-235-0681 TX 15757 Coit Rd https://www.walmart.com/store/8930/dallas-tx/d... 75248 4653 Murray US 40.6498 -111.849 Murray Pickup only ... 801-278-8290 UT 5596 S Van Winkle Expy https://www.walmart.com/store/8862/murray-ut/d... 84117 ``` {% endtab %} {% tab title="Information" %} ``` [4654 rows x 11 columns] Int64Index: 4654 entries, 0 to 4653 Data columns (total 11 columns): # Column Non-Null Count Dtype --- ------ -------------- ----- 0 city 4654 non-null object 1 country 4654 non-null object 2 latitude 4654 non-null float64 3 longitude 4654 non-null float64 4 name 4654 non-null object 5 open_hours 4631 non-null object 6 phone_number_1 4654 non-null object 7 state 4654 non-null object 8 street_address 4654 non-null object 9 url 4654 non-null object 10 zip_code 4654 non-null int64 dtypes: float64(2), int64(1), object(8) memory usage: 436.3+ KB ``` {% endtab %} {% endtabs %}