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U.S. Weather History: KNYC.csv

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 Downloades 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

365 rows sorted by record_precipitation

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Suggested facets: average_precipitation

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 ▼
71 2014-9-9 68 63 73 63 78 48 94 1883 1915 0.0 0.13 0.86
329 2015-5-25 75 64 85 57 73 41 95 1925 1880 0.0 0.15 0.86
303 2015-4-29 64 50 78 49 66 32 89 1874 1974 0.0 0.14 0.91
257 2015-3-14 46 40 51 35 49 15 75 1896 1946 0.81 0.14 1.02
213 2015-1-29 28 19 36 27 39 0 69 1873 2002 0.02 0.11 1.03
321 2015-5-17 74 64 83 54 71 39 92 1956 1974 0.02 0.13 1.05
9 2014-7-9 80 71 88 69 84 54 106 1963 1936 0.09 0.14 1.09
285 2015-4-11 51 44 57 43 60 24 84 1909 1955 0.0 0.16 1.1
306 2015-5-2 61 48 74 50 67 37 90 1903 2001 0.0 0.12 1.1
153 2014-11-30 50 45 55 37 49 7 70 1875 1991 0.0 0.15 1.11
350 2015-6-15 74 64 83 64 79 48 96 1933 1994 0.57 0.15 1.13
346 2015-6-11 81 72 89 62 78 46 95 1972 1973 0.0 0.16 1.14
223 2015-2-8 33 29 37 28 40 -7 61 1934 1965 0.0 0.11 1.15
319 2015-5-15 65 55 75 54 71 42 90 1947 1900 0.0 0.13 1.16
332 2015-5-28 78 70 85 58 74 43 94 1961 1959 0.0 0.14 1.16
214 2015-1-30 29 19 38 27 39 2 64 1873 2006 0.06 0.11 1.19
243 2015-2-28 21 13 29 31 45 5 67 1934 1976 0.0 0.12 1.21
141 2014-11-18 35 24 45 41 53 18 73 1936 1928 0.0 0.14 1.24
192 2015-1-8 15 8 21 27 38 2 65 1968 1998 0.0 0.11 1.25
326 2015-5-22 65 55 74 56 72 44 96 1990 1941 0.0 0.15 1.25
287 2015-4-13 59 50 68 44 60 25 88 1874 1977 0.0 0.16 1.26
199 2015-1-15 30 25 35 27 38 0 67 1957 1932 0.0 0.13 1.27
158 2014-12-5 39 34 44 35 47 11 70 1926 2001 0.51 0.14 1.28
330 2015-5-26 78 67 88 57 74 42 95 1967 1880 0.0 0.15 1.28
360 2015-6-25 74 65 83 66 82 50 99 1873 1952 0.0 0.14 1.28
291 2015-4-17 63 55 71 45 62 28 96 1875 2002 0.08 0.15 1.29
171 2014-12-18 40 37 42 31 42 -1 63 1919 1984 0.0 0.12 1.3
178 2014-12-25 53 44 62 29 40 -1 64 1980 1982 0.09 0.13 1.3
351 2015-6-16 72 65 79 64 80 52 97 1927 1891 0.27 0.15 1.31
144 2014-11-21 33 28 37 40 52 16 74 1879 1900 0.0 0.14 1.33
168 2014-12-15 43 37 48 32 43 6 67 1874 2008 0.0 0.13 1.34
181 2014-12-28 49 43 54 29 40 8 65 1917 1982 0.1 0.12 1.35
281 2015-4-7 52 42 62 42 58 21 92 1982 2010 0.15 0.16 1.35
148 2014-11-25 60 51 68 39 50 19 73 1938 1979 0.0 0.13 1.36
201 2015-1-17 25 17 32 27 38 -2 63 1977 1990 0.0 0.12 1.36
16 2014-7-16 75 68 81 69 84 56 99 1946 1980 0.0 0.16 1.38
72 2014-9-10 72 63 80 63 77 43 97 1883 1983 0.0 0.13 1.38
238 2015-2-23 23 8 38 30 43 5 70 1889 1985 0.0 0.12 1.38
355 2015-6-20 70 64 75 65 81 49 98 1914 1923 0.0 0.13 1.39
231 2015-2-16 12 3 21 29 42 1 71 1888 1954 0.0 0.12 1.4
134 2014-11-11 57 49 64 43 56 28 74 1933 1949 0.0 0.12 1.41
204 2015-1-20 36 32 40 27 38 0 61 1994 2006 0.0 0.11 1.41
177 2014-12-24 51 44 58 30 41 6 63 1983 1996 0.8 0.13 1.42
193 2015-1-9 26 19 33 27 38 -1 64 1968 1937 0.07 0.13 1.42
260 2015-3-17 46 34 57 35 50 9 75 1916 1945 0.02 0.15 1.42
269 2015-3-26 52 42 62 38 53 20 76 1960 1922 0.32 0.15 1.42
313 2015-5-9 64 57 70 52 69 35 94 1947 1979 0.0 0.13 1.42
220 2015-2-5 28 14 42 28 40 -6 70 1918 1991 0.0 0.11 1.43
36 2014-8-5 81 71 90 69 84 56 101 1951 1944 0.0 0.16 1.44
127 2014-11-4 61 53 68 45 58 25 78 1879 1975 0.0 0.13 1.44
197 2015-1-13 27 17 36 27 38 -3 68 1914 1932 0.0 0.12 1.44
200 2015-1-16 32 20 43 27 38 1 58 2004 1995 0.0 0.12 1.44
195 2015-1-11 28 18 37 27 38 3 63 1968 1975 0.0 0.12 1.46
310 2015-5-6 66 59 73 51 68 32 92 1891 1986 0.0 0.13 1.46
359 2015-6-24 76 68 84 66 82 52 96 1932 1888 0.0 0.13 1.46
129 2014-11-6 53 48 57 44 57 27 74 1879 1948 0.37 0.14 1.47
343 2015-6-8 71 63 79 61 77 47 95 1932 1933 0.06 0.16 1.47
232 2015-2-17 21 14 27 29 42 -5 67 1896 1976 0.14 0.11 1.49
189 2015-1-5 35 21 49 27 38 -4 64 1904 1993 0.0 0.12 1.5
233 2015-2-18 26 19 33 29 42 0 68 1979 1981 0.0 0.11 1.5
114 2014-10-22 54 50 58 48 62 30 88 1940 1979 1.51 0.15 1.51
215 2015-1-31 20 13 26 27 39 -1 63 1920 1947 0.0 0.12 1.51
46 2014-8-15 67 61 73 68 83 54 97 1964 1988 0.0 0.14 1.52
140 2014-11-17 46 40 52 41 53 19 71 1933 1953 1.54 0.14 1.54
161 2014-12-8 31 24 37 34 45 10 65 1882 1927 0.0 0.14 1.54
95 2014-10-3 64 56 71 54 68 38 87 1974 1919 0.0 0.14 1.55
218 2015-2-3 20 13 26 27 39 0 64 1955 1991 0.0 0.11 1.55
309 2015-5-5 76 66 85 51 68 34 90 1891 1980 0.0 0.13 1.55
242 2015-2-27 24 18 30 31 44 5 72 1900 1997 0.0 0.12 1.56
172 2014-12-19 35 31 38 31 42 -1 58 1884 1931 0.0 0.12 1.58
229 2015-2-14 24 16 32 29 41 2 63 1916 1946 0.02 0.11 1.59
14 2014-7-14 78 72 84 69 84 58 100 1926 1954 0.46 0.16 1.6
159 2014-12-6 45 39 50 35 46 11 71 1871 2001 1.22 0.13 1.6
165 2014-12-12 35 32 38 33 44 5 68 1988 1931 0.0 0.13 1.6
266 2015-3-23 31 23 38 37 52 12 76 1875 1923 0.0 0.16 1.6
176 2014-12-23 45 43 46 30 41 -1 66 1883 1990 0.16 0.13 1.61
163 2014-12-10 36 32 40 34 45 3 70 1876 1946 0.08 0.14 1.62
253 2015-3-10 46 39 53 33 48 12 74 1929 2006 0.46 0.13 1.62
156 2014-12-3 44 41 46 36 47 9 69 1976 1998 0.06 0.15 1.63
25 2014-7-25 74 66 82 69 84 57 97 1953 1999 0.0 0.15 1.64
122 2014-10-30 53 47 59 46 59 31 82 1925 1961 0.0 0.13 1.64
190 2015-1-6 21 19 22 27 38 -2 72 1896 2007 0.05 0.13 1.65
247 2015-3-4 40 35 45 32 46 7 70 1943 1974 0.25 0.13 1.65
179 2014-12-26 45 40 50 29 40 3 63 1914 1982 0.0 0.12 1.66
227 2015-2-12 28 16 40 28 41 -3 62 1914 1999 0.0 0.11 1.66
307 2015-5-3 66 51 80 50 67 36 90 1874 2001 0.0 0.13 1.66
317 2015-5-13 62 53 70 53 70 39 89 1895 1956 0.0 0.12 1.66
315 2015-5-11 77 70 84 52 70 36 92 1913 1993 0.0 0.12 1.67
299 2015-4-25 50 38 62 48 65 29 91 1919 1915 0.0 0.14 1.68
124 2014-11-1 45 42 47 46 59 30 84 1885 1950 0.35 0.14 1.69
183 2014-12-30 31 28 34 28 39 -13 65 1917 1984 0.0 0.12 1.69
239 2015-2-24 14 4 24 30 44 -4 75 1873 1985 0.0 0.12 1.69
363 2015-6-28 68 62 73 67 83 54 96 1995 1991 0.29 0.13 1.69
107 2014-10-15 73 69 77 50 64 32 84 1876 1956 0.69 0.14 1.7
125 2014-11-2 45 41 48 45 58 30 83 1887 1950 0.0 0.14 1.7
133 2014-11-10 53 44 61 43 56 27 73 1914 1985 0.0 0.13 1.7
206 2015-1-22 36 31 40 27 38 0 61 1888 1959 0.0 0.12 1.7
356 2015-6-21 80 71 88 65 81 49 97 1897 1988 0.64 0.14 1.7
348 2015-6-13 79 72 86 63 79 51 96 1953 1961 0.0 0.16 1.71
154 2014-12-1 54 42 65 37 48 9 70 1875 2006 0.09 0.14 1.72

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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
)
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