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 record_max_temp_year

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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
186 2015-1-2 39 35 42 28 39 2 68 1918 1876 0.0 0.12 1.92
194 2015-1-10 20 16 23 27 38 -6 60 1875 1876 0.0 0.12 1.72
135 2014-11-12 56 47 65 43 55 26 76 1926 1879 0.0 0.12 2.39
164 2014-12-11 35 31 38 33 44 6 64 1880 1879 0.01 0.14 2.41
248 2015-3-5 30 19 40 32 46 3 72 1872 1880 0.76 0.13 1.81
329 2015-5-25 75 64 85 57 73 41 95 1925 1880 0.0 0.15 0.86
330 2015-5-26 78 67 88 57 74 42 95 1967 1880 0.0 0.15 1.28
331 2015-5-27 78 70 85 57 74 41 96 1961 1880 0.08 0.14 2.62
68 2014-9-6 79 67 91 64 79 48 97 1924 1881 0.11 0.13 3.26
69 2014-9-7 73 65 81 64 78 46 101 1888 1881 0.0 0.14 2.07
90 2014-9-28 74 64 84 56 70 41 88 1947 1881 0.0 0.16 3.84
167 2014-12-14 42 38 46 32 43 12 67 1976 1881 0.0 0.13 2.22
316 2015-5-12 75 64 86 53 70 40 93 1907 1881 0.0 0.13 1.84
358 2015-6-23 83 75 90 66 81 49 96 1918 1888 0.02 0.13 1.75
359 2015-6-24 76 68 84 66 82 52 96 1932 1888 0.0 0.13 1.46
196 2015-1-12 37 35 39 27 38 2 64 1981 1890 0.36 0.13 2.35
241 2015-2-26 27 21 32 31 44 7 65 1990 1890 0.0 0.12 1.87
255 2015-3-12 42 36 47 34 48 8 71 1888 1890 0.0 0.13 2.33
80 2014-9-18 67 57 76 60 75 44 91 1990 1891 0.0 0.15 3.92
351 2015-6-16 72 65 79 64 80 52 97 1927 1891 0.27 0.15 1.31
278 2015-4-4 51 42 60 41 57 21 80 1874 1892 0.01 0.16 1.99
83 2014-9-21 71 67 75 59 73 40 95 1871 1895 0.15 0.15 5.54
85 2014-9-23 62 52 71 58 73 41 97 1947 1895 0.0 0.14 8.28
336 2015-6-1 55 51 58 59 75 44 96 1945 1895 0.72 0.16 2.6
337 2015-6-2 53 50 55 59 76 48 96 1946 1895 0.37 0.16 2.79
338 2015-6-3 61 52 70 60 76 45 95 1929 1895 0.0 0.16 3.01
150 2014-11-27 36 34 38 38 50 12 72 1932 1896 0.02 0.13 2.15
108 2014-10-16 66 61 71 50 64 34 87 1876 1897 1.11 0.14 2.15
144 2014-11-21 33 28 37 40 52 16 74 1879 1900 0.0 0.14 1.33
318 2015-5-14 62 50 73 53 70 40 88 1878 1900 0.0 0.12 3.38
319 2015-5-15 65 55 75 54 71 42 90 1947 1900 0.0 0.13 1.16
1 2014-7-1 81 72 89 68 83 52 100 1943 1901 0.0 0.12 2.17
207 2015-1-23 34 28 39 27 38 -3 62 1936 1906 0.0 0.11 2.55
191 2015-1-7 16 9 23 27 38 4 64 2014 1907 0.0 0.12 2.67
84 2014-9-22 63 55 71 59 73 41 95 1904 1914 0.0 0.15 2.34
71 2014-9-9 68 63 73 63 78 48 94 1883 1915 0.0 0.13 0.86
78 2014-9-16 64 58 70 61 75 47 93 1966 1915 0.37 0.15 5.02
299 2015-4-25 50 38 62 48 65 29 91 1919 1915 0.0 0.14 1.68
301 2015-4-27 56 49 62 48 65 36 92 1932 1915 0.0 0.14 2.04
53 2014-8-22 72 65 79 67 82 52 95 1895 1916 0.06 0.14 1.85
54 2014-8-23 72 67 77 67 82 51 92 1923 1916 0.01 0.14 3.03
101 2014-10-9 62 55 68 52 66 37 86 2000 1916 0.0 0.15 7.33
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
275 2015-4-1 42 32 51 40 56 12 83 1923 1917 0.0 0.16 1.89
38 2014-8-7 75 66 83 69 84 57 104 1994 1918 0.0 0.15 2.18
262 2015-3-19 36 29 43 36 51 8 76 1967 1918 0.0 0.15 2.19
70 2014-9-8 70 65 75 64 78 54 93 1955 1919 0.0 0.13 4.86
95 2014-10-3 64 56 71 54 68 38 87 1974 1919 0.0 0.14 1.55
120 2014-10-28 63 53 72 47 60 29 83 1976 1919 0.0 0.13 2.49
106 2014-10-14 70 63 76 50 64 37 84 1988 1920 0.0 0.15 1.76
113 2014-10-21 61 55 67 48 62 32 84 1974 1920 0.11 0.14 2.17
142 2014-11-19 29 22 36 41 53 18 72 1936 1921 0.0 0.14 1.95
264 2015-3-21 38 29 47 37 51 10 84 1885 1921 0.0 0.15 2.37
269 2015-3-26 52 42 62 38 53 20 76 1960 1922 0.32 0.15 1.42
284 2015-4-10 48 39 56 43 59 28 86 1997 1922 0.17 0.17 4.31
166 2014-12-13 39 34 44 33 44 8 64 1960 1923 0.0 0.13 3.03
266 2015-3-23 31 23 38 37 52 12 76 1875 1923 0.0 0.16 1.6
295 2015-4-21 59 52 65 47 63 26 87 1875 1923 0.2 0.14 2.28
355 2015-6-20 70 64 75 65 81 49 98 1914 1923 0.0 0.13 1.39
339 2015-6-4 60 54 65 60 76 48 99 1926 1925 0.0 0.16 2.75
340 2015-6-5 63 55 70 60 76 47 99 1945 1925 0.13 0.16 2.8
341 2015-6-6 68 60 76 61 77 47 98 1945 1925 0.19 0.16 2.62
342 2015-6-7 65 55 74 61 77 47 96 1897 1925 0.0 0.16 4.16
77 2014-9-15 63 55 71 61 76 45 92 1913 1927 0.0 0.15 4.16
93 2014-10-1 63 61 65 55 69 36 88 1947 1927 0.02 0.15 4.98
94 2014-10-2 66 61 70 55 69 39 90 1886 1927 0.0 0.14 2.16
161 2014-12-8 31 24 37 34 45 10 65 1882 1927 0.0 0.14 1.54
294 2015-4-20 52 46 57 46 63 24 90 1897 1927 1.37 0.14 1.96
110 2014-10-18 63 56 70 49 63 35 82 1974 1928 0.0 0.14 2.45
139 2014-11-16 40 35 45 42 54 17 72 1933 1928 0.03 0.13 2.39
141 2014-11-18 35 24 45 41 53 18 73 1936 1928 0.0 0.14 1.24
279 2015-4-5 52 42 61 41 57 20 80 1874 1928 0.0 0.16 2.76
65 2014-9-3 79 72 86 65 80 50 99 1893 1929 0.0 0.13 3.32
66 2014-9-4 78 69 87 65 79 47 97 1883 1929 0.0 0.14 3.48
353 2015-6-18 68 64 71 65 80 48 95 1950 1929 0.0 0.14 2.3
236 2015-2-21 23 13 32 30 43 4 68 1896 1930 0.61 0.11 1.86
240 2015-2-25 29 20 37 31 44 1 75 1914 1930 0.0 0.11 2.11
76 2014-9-14 62 53 71 62 76 46 93 1975 1931 0.0 0.14 3.82
136 2014-11-13 42 36 48 43 55 22 73 1873 1931 0.2 0.13 2.06
145 2014-11-22 36 28 44 40 52 13 72 1880 1931 0.0 0.14 2.03
146 2014-11-23 50 43 57 40 51 14 72 1880 1931 0.0 0.14 1.84
165 2014-12-12 35 32 38 33 44 5 68 1988 1931 0.0 0.13 1.6
172 2014-12-19 35 31 38 31 42 -1 58 1884 1931 0.0 0.12 1.58
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
199 2015-1-15 30 25 35 27 38 0 67 1957 1932 0.0 0.13 1.27
31 2014-7-31 75 68 82 69 84 57 102 1914 1933 0.0 0.17 2.29
32 2014-8-1 78 71 84 69 84 59 100 1964 1933 0.0 0.16 2.85
89 2014-9-27 72 60 83 57 71 41 90 1957 1933 0.0 0.15 3.13
343 2015-6-8 71 63 79 61 77 47 95 1932 1933 0.06 0.16 1.47
344 2015-6-9 76 68 83 62 78 47 97 1980 1933 0.01 0.16 2.55
364 2015-6-29 70 63 76 67 83 52 101 1919 1934 0.0 0.12 2.57
249 2015-3-6 20 12 27 32 46 6 68 1872 1935 0.0 0.13 2.63
9 2014-7-9 80 71 88 69 84 54 106 1963 1936 0.09 0.14 1.09
322 2015-5-18 68 60 75 55 71 41 90 1973 1936 0.0 0.13 2.18
193 2015-1-9 26 19 33 27 38 -1 64 1968 1937 0.07 0.13 1.42
109 2014-10-17 65 59 71 50 63 33 90 1886 1938 0.0 0.14 2.28
130 2014-11-7 47 40 53 44 57 29 78 1930 1938 0.0 0.13 2.96
222 2015-2-7 33 25 40 28 40 1 54 1910 1938 0.02 0.11 2.96

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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
);