This table contains data and code behind the story What 12 Months Of Record-Setting Temperatures Looks Like Across The U.S..

Code

Code file Description
wunderground_scraper.py Downloads weather data web pages from Weather Underground
wunderground_parser.py Parses the weather data from Weather Underground into a flat CSV file
visualize_weather.py Creates the visualization of the weather data

Data

Column Description
date The date of the weather record, formatted YYYY-M-D
actual_mean_temp The measured average temperature for that day
actual_min_temp The measured minimum temperature for that day
actual_max_temp The measured maximum temperature for that day
average_min_temp The average minimum temperature on that day since 1880
average_max_temp The average maximum temperature on that day since 1880
record_min_temp The lowest ever temperature on that day since 1880
record_max_temp The highest ever temperature on that day since 1880
record_min_temp_year The year that the lowest ever temperature occurred
record_max_temp_year The year that the highest ever temperature occurred
actual_precipitation The measured amount of rain or snow for that day
average_precipitation The average amount of rain or snow on that day since 1880
record_precipitation The highest amount of rain or snow on that day since 1880

Source: Weather Underground

Data license: CC Attribution 4.0 License · Data source: fivethirtyeight/data on GitHub · About: simonw/fivethirtyeight-datasette

365 rows sorted by average_precipitation

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Suggested facets: average_precipitation, date (date)

Link rowid date actual_mean_temp actual_min_temp actual_max_temp average_min_temp average_max_temp record_min_temp record_max_temp record_min_temp_year record_max_temp_year actual_precipitation average_precipitation ▼ record_precipitation
219 2015-2-4 34 24 43 28 40 0 68 1918 1991 0.0 0.1 2.1
224 2015-2-9 27 25 29 28 40 -15 63 1934 1990 0.09 0.1 1.74
226 2015-2-11 28 22 34 28 41 -2 65 1899 1960 0.0 0.1 2.74
228 2015-2-13 15 8 21 29 41 -1 64 1914 1951 0.0 0.1 2.42
230 2015-2-15 15 4 25 29 42 -8 73 1943 1949 0.0 0.1 1.73
182 2014-12-29 39 34 44 28 39 -6 70 1917 1984 0.0 0.11 2.52
184 2014-12-31 30 27 32 28 39 -7 63 1917 1965 0.0 0.11 2.31
192 2015-1-8 15 8 21 27 38 2 65 1968 1998 0.0 0.11 1.25
202 2015-1-18 37 31 42 27 38 0 66 1982 1990 2.1 0.11 2.1
204 2015-1-20 36 32 40 27 38 0 61 1994 2006 0.0 0.11 1.41
207 2015-1-23 34 28 39 27 38 -3 62 1936 1906 0.0 0.11 2.55
208 2015-1-24 36 33 39 27 38 -6 68 1882 1967 0.72 0.11 2.18
209 2015-1-25 37 31 42 27 38 2 60 1945 1967 0.0 0.11 1.8
210 2015-1-26 27 22 31 27 39 3 72 1927 1950 0.48 0.11 2.19
211 2015-1-27 25 20 30 27 39 -1 69 1927 1916 0.36 0.11 1.94
212 2015-1-28 25 16 34 27 39 -2 66 1925 1916 0.0 0.11 1.87
213 2015-1-29 28 19 36 27 39 0 69 1873 2002 0.02 0.11 1.03
214 2015-1-30 29 19 38 27 39 2 64 1873 2006 0.06 0.11 1.19
216 2015-2-1 28 20 36 27 39 -2 67 1920 1989 0.03 0.11 2.12
217 2015-2-2 24 14 34 27 39 -3 59 1881 1988 1.02 0.11 2.98
218 2015-2-3 20 13 26 27 39 0 64 1955 1991 0.0 0.11 1.55
220 2015-2-5 28 14 42 28 40 -6 70 1918 1991 0.0 0.11 1.43
221 2015-2-6 20 12 27 28 40 -4 68 1895 2008 0.0 0.11 2.74
222 2015-2-7 33 25 40 28 40 1 54 1910 1938 0.02 0.11 2.96
223 2015-2-8 33 29 37 28 40 -7 61 1934 1965 0.0 0.11 1.15
225 2015-2-10 33 26 40 28 41 -6 61 1899 2001 0.01 0.11 2.63
227 2015-2-12 28 16 40 28 41 -3 62 1914 1999 0.0 0.11 1.66
229 2015-2-14 24 16 32 29 41 2 63 1916 1946 0.02 0.11 1.59
232 2015-2-17 21 14 27 29 42 -5 67 1896 1976 0.14 0.11 1.49
233 2015-2-18 26 19 33 29 42 0 68 1979 1981 0.0 0.11 1.5
234 2015-2-19 18 8 27 30 42 1 66 1936 1997 0.0 0.11 2.15
235 2015-2-20 11 2 19 30 43 2 69 2015 1939 0.0 0.11 3.07
236 2015-2-21 23 13 32 30 43 4 68 1896 1930 0.61 0.11 1.86
237 2015-2-22 38 32 43 30 43 8 69 1963 1997 0.1 0.11 2.39
240 2015-2-25 29 20 37 31 44 1 75 1914 1930 0.0 0.11 2.11
1 2014-7-1 81 72 89 68 83 52 100 1943 1901 0.0 0.12 2.17
3 2014-7-3 78 69 87 68 83 54 103 1933 1966 1.78 0.12 2.8
5 2014-7-5 72 63 81 68 84 53 101 1979 1999 0.0 0.12 3.07
57 2014-8-26 80 70 89 67 81 53 103 1887 1948 0.0 0.12 3.24
60 2014-8-29 71 61 80 66 81 50 99 1986 1953 0.0 0.12 2.68
61 2014-8-30 73 65 80 66 81 50 98 1965 1973 0.0 0.12 2.3
62 2014-8-31 82 73 90 66 80 50 100 1976 1953 0.62 0.12 3.76
131 2014-11-8 42 36 48 44 57 29 76 1886 1975 0.0 0.12 7.4
134 2014-11-11 57 49 64 43 56 28 74 1933 1949 0.0 0.12 1.41
135 2014-11-12 56 47 65 43 55 26 76 1926 1879 0.0 0.12 2.39
169 2014-12-16 44 38 49 32 43 7 63 1876 1971 0.2 0.12 2.25
171 2014-12-18 40 37 42 31 42 -1 63 1919 1984 0.0 0.12 1.3
172 2014-12-19 35 31 38 31 42 -1 58 1884 1931 0.0 0.12 1.58
173 2014-12-20 32 30 33 31 42 -4 60 1942 2002 0.0 0.12 1.82
175 2014-12-22 40 35 44 30 41 2 71 1872 2013 0.04 0.12 2.18
179 2014-12-26 45 40 50 29 40 3 63 1914 1982 0.0 0.12 1.66
180 2014-12-27 50 44 55 29 40 6 63 1872 1949 0.0 0.12 2.14
181 2014-12-28 49 43 54 29 40 8 65 1917 1982 0.1 0.12 1.35
183 2014-12-30 31 28 34 28 39 -13 65 1917 1984 0.0 0.12 1.69
185 2015-1-1 33 27 39 28 39 -4 62 1918 1966 0.0 0.12 2.05
186 2015-1-2 39 35 42 28 39 2 68 1918 1876 0.0 0.12 1.92
187 2015-1-3 38 33 42 28 39 -4 64 1879 2000 0.71 0.12 2.42
188 2015-1-4 49 41 56 27 39 -3 66 1918 1950 0.3 0.12 2.73
189 2015-1-5 35 21 49 27 38 -4 64 1904 1993 0.0 0.12 1.5
191 2015-1-7 16 9 23 27 38 4 64 2014 1907 0.0 0.12 2.67
194 2015-1-10 20 16 23 27 38 -6 60 1875 1876 0.0 0.12 1.72
195 2015-1-11 28 18 37 27 38 3 63 1968 1975 0.0 0.12 1.46
197 2015-1-13 27 17 36 27 38 -3 68 1914 1932 0.0 0.12 1.44
198 2015-1-14 24 16 32 27 38 -5 70 1914 1932 0.0 0.12 2.06
200 2015-1-16 32 20 43 27 38 1 58 2004 1995 0.0 0.12 1.44
201 2015-1-17 25 17 32 27 38 -2 63 1977 1990 0.0 0.12 1.36
203 2015-1-19 39 36 42 27 38 -3 64 1875 1951 0.0 0.12 2.39
205 2015-1-21 31 25 36 27 38 -2 63 1985 2006 0.0 0.12 3.45
206 2015-1-22 36 31 40 27 38 0 61 1888 1959 0.0 0.12 1.7
215 2015-1-31 20 13 26 27 39 -1 63 1920 1947 0.0 0.12 1.51
231 2015-2-16 12 3 21 29 42 1 71 1888 1954 0.0 0.12 1.4
238 2015-2-23 23 8 38 30 43 5 70 1889 1985 0.0 0.12 1.38
239 2015-2-24 14 4 24 30 44 -4 75 1873 1985 0.0 0.12 1.69
241 2015-2-26 27 21 32 31 44 7 65 1990 1890 0.0 0.12 1.87
242 2015-2-27 24 18 30 31 44 5 72 1900 1997 0.0 0.12 1.56
243 2015-2-28 21 13 29 31 45 5 67 1934 1976 0.0 0.12 1.21
245 2015-3-2 33 27 39 32 45 9 72 1891 1972 0.0 0.12 2.41
246 2015-3-3 30 22 37 32 45 11 65 2003 1991 0.67 0.12 2.25
256 2015-3-13 37 31 43 34 49 6 85 1888 1990 0.0 0.12 3.86
305 2015-5-1 56 49 63 50 67 35 87 1880 2001 0.0 0.12 2.48
306 2015-5-2 61 48 74 50 67 37 90 1903 2001 0.0 0.12 1.1
312 2015-5-8 69 56 82 52 69 37 91 1947 2000 0.0 0.12 3.02
315 2015-5-11 77 70 84 52 70 36 92 1913 1993 0.0 0.12 1.67
317 2015-5-13 62 53 70 53 70 39 89 1895 1956 0.0 0.12 1.66
318 2015-5-14 62 50 73 53 70 40 88 1878 1900 0.0 0.12 3.38
362 2015-6-27 65 58 71 67 82 55 101 1940 1966 1.12 0.12 2.11
364 2015-6-29 70 63 76 67 83 52 101 1919 1934 0.0 0.12 2.57
2 2014-7-2 82 72 91 68 83 56 100 2001 1966 0.96 0.13 1.79
4 2014-7-4 70 65 74 68 84 55 102 1986 1949 0.14 0.13 1.76
6 2014-7-6 75 66 84 68 84 54 103 1979 2010 0.0 0.13 1.97
7 2014-7-7 81 72 90 68 84 56 100 1914 2010 0.04 0.13 3.13
58 2014-8-27 80 70 90 67 81 50 101 1885 1948 0.0 0.13 4.16
59 2014-8-28 74 66 82 66 81 50 100 1885 1948 0.0 0.13 3.99
63 2014-9-1 82 75 88 66 80 51 97 1872 1953 0.0 0.13 3.84
64 2014-9-2 85 77 92 65 80 51 102 1886 1953 0.0 0.13 2.12
65 2014-9-3 79 72 86 65 80 50 99 1893 1929 0.0 0.13 3.32
67 2014-9-5 80 72 87 64 79 51 94 1963 1985 0.0 0.13 2.45
68 2014-9-6 79 67 91 64 79 48 97 1924 1881 0.11 0.13 3.26
70 2014-9-8 70 65 75 64 78 54 93 1955 1919 0.0 0.13 4.86
71 2014-9-9 68 63 73 63 78 48 94 1883 1915 0.0 0.13 0.86

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CREATE TABLE "us-weather-history/KNYC" (
"date" TEXT,
  "actual_mean_temp" INTEGER,
  "actual_min_temp" INTEGER,
  "actual_max_temp" INTEGER,
  "average_min_temp" INTEGER,
  "average_max_temp" INTEGER,
  "record_min_temp" INTEGER,
  "record_max_temp" INTEGER,
  "record_min_temp_year" INTEGER,
  "record_max_temp_year" INTEGER,
  "actual_precipitation" REAL,
  "average_precipitation" REAL,
  "record_precipitation" REAL
);