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U.S. Weather History: KCQT.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

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Suggested facets: average_min_temp, average_max_temp, record_min_temp, actual_precipitation, 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
1 2014-7-1 70 63 77 63 82 52 107 1886 1985 0.0 0.0 0.09
2 2014-7-2 70 62 77 63 82 51 102 1887 1985 0.0 0.0 0.0
3 2014-7-3 72 63 81 63 82 52 100 1902 1985 0.0 0.0 0.0
4 2014-7-4 72 62 82 63 82 53 103 1900 1907 0.0 0.0 0.07
5 2014-7-5 75 64 86 63 82 50 100 1886 1907 0.0 0.0 0.02
6 2014-7-6 73 64 81 63 82 51 94 1894 1992 0.0 0.0 0.03
7 2014-7-7 77 64 89 63 83 51 96 1894 1954 0.0 0.0 0.02
8 2014-7-8 77 68 86 63 83 51 95 1894 1886 0.0 0.0 0.13
9 2014-7-9 75 67 82 63 83 52 100 1901 1985 0.0 0.0 0.05
10 2014-7-10 76 66 85 63 83 55 103 1903 1959 0.0 0.0 0.0
11 2014-7-11 73 65 80 64 83 52 97 1878 1959 0.0 0.0 0.04
12 2014-7-12 74 65 82 64 83 49 98 1888 1953 0.0 0.0 0.05
13 2014-7-13 75 67 82 64 83 51 98 1888 1990 0.0 0.0 0.02
14 2014-7-14 74 68 80 64 83 52 98 1908 1984 0.0 0.0 0.24
15 2014-7-15 76 69 82 64 83 50 98 1893 1886 0.0 0.0 0.0
16 2014-7-16 74 66 81 64 83 52 96 1894 1930 0.0 0.01 0.02
17 2014-7-17 73 65 80 64 83 52 98 1894 1998 0.0 0.0 0.01
18 2014-7-18 72 64 79 64 84 53 97 1884 1936 0.0 0.0 0.36
19 2014-7-19 71 66 75 64 84 52 97 1884 1960 0.0 0.0 0.02
20 2014-7-20 73 66 80 64 84 52 100 1892 1960 0.0 0.0 0.0
21 2014-7-21 74 66 81 64 84 53 96 1903 1960 0.0 0.0 0.0
22 2014-7-22 75 65 85 64 84 52 101 1880 2006 0.0 0.0 0.1
23 2014-7-23 77 65 88 64 84 53 97 1903 1890 0.0 0.0 0.08
24 2014-7-24 79 65 92 64 84 52 103 1882 1891 0.0 0.0 0.0
25 2014-7-25 79 69 88 64 84 52 109 1903 1891 0.0 0.0 0.04
26 2014-7-26 77 68 86 64 84 52 100 1886 1891 0.0 0.0 0.04
27 2014-7-27 76 67 84 64 84 52 102 1903 1972 0.0 0.0 0.0
28 2014-7-28 78 68 88 64 84 52 101 1883 1995 0.0 0.0 0.01
29 2014-7-29 78 68 88 64 84 53 100 1909 1995 0.0 0.0 0.0
30 2014-7-30 79 68 90 64 84 54 100 1894 1980 0.0 0.0 0.02
31 2014-7-31 77 67 87 64 84 52 100 1885 1972 0.0 0.0 0.01
32 2014-8-1 76 66 85 64 84 54 99 1888 1959 0.0 0.0 0.01
33 2014-8-2 78 65 90 64 84 51 98 1888 1997 0.02 0.0 0.02
34 2014-8-3 79 72 85 64 84 52 100 1913 1918 0.02 0.0 0.02
35 2014-8-4 76 65 87 64 84 52 94 1912 1971 0.0 0.0 0.05
36 2014-8-5 73 63 82 64 84 52 100 1887 1997 0.0 0.0 0.09
37 2014-8-6 70 63 77 64 84 50 105 1883 1983 0.0 0.01 0.02
38 2014-8-7 73 64 81 64 84 54 99 1894 1884 0.0 0.0 0.11
39 2014-8-8 74 65 82 64 84 54 100 1916 1881 0.0 0.0 0.02
40 2014-8-9 75 67 82 64 84 53 100 1889 1998 0.0 0.0 0.19
41 2014-8-10 76 66 85 64 84 54 99 1897 1882 0.0 0.0 0.04
42 2014-8-11 75 65 85 64 84 53 98 1894 1879 0.0 0.0 0.02
43 2014-8-12 75 66 84 64 84 52 104 1894 1994 0.0 0.0 0.32
44 2014-8-13 73 65 81 64 84 54 102 1892 1994 0.0 0.0 0.13
45 2014-8-14 74 65 83 64 84 54 97 1887 1885 0.0 0.01 0.01
46 2014-8-15 76 63 89 64 84 52 98 1894 1994 0.0 0.0 0.4
47 2014-8-16 78 66 90 64 84 52 98 1883 1890 0.0 0.0 0.19
48 2014-8-17 78 66 89 64 85 52 104 1887 1885 0.0 0.0 2.06
49 2014-8-18 76 65 86 64 85 52 102 1887 1885 0.0 0.0 0.44
50 2014-8-19 76 69 82 64 85 54 106 1916 1885 0.0 0.0 0.14
51 2014-8-20 76 67 84 64 85 51 97 1900 1986 0.0 0.0 0.03
52 2014-8-21 73 65 80 64 85 53 96 1899 1982 0.0 0.0 0.0
53 2014-8-22 74 66 81 64 85 52 102 1901 1972 0.0 0.01 0.04
54 2014-8-23 76 66 85 64 85 54 100 1905 1968 0.0 0.0 0.0
55 2014-8-24 75 67 83 64 85 53 96 1900 1931 0.0 0.0 0.05
56 2014-8-25 72 64 80 64 85 52 102 1909 1985 0.0 0.0 0.01
57 2014-8-26 75 65 84 64 85 53 98 1885 1981 0.0 0.0 0.1
58 2014-8-27 79 66 91 64 85 53 103 1902 1981 0.0 0.0 0.96
59 2014-8-28 80 68 91 64 85 52 99 1902 1995 0.0 0.01 0.1
60 2014-8-29 78 65 90 64 85 51 102 1901 1884 0.0 0.0 0.08
61 2014-8-30 77 65 89 64 85 49 101 1901 1998 0.0 0.0 0.21
62 2014-8-31 78 69 87 64 85 52 103 1895 1967 0.0 0.0 0.61
63 2014-9-1 78 70 85 64 85 49 110 1901 1955 0.0 0.0 0.41
64 2014-9-2 76 68 84 64 85 51 108 1881 1955 0.0 0.0 0.02
65 2014-9-3 75 67 83 64 85 51 103 1892 1988 0.0 0.0 0.05
66 2014-9-4 73 66 80 64 85 52 110 1892 1988 0.0 0.01 0.3
67 2014-9-5 75 66 83 64 85 50 105 1898 1984 0.0 0.0 0.32
68 2014-9-6 76 65 86 64 84 48 102 1898 1955 0.0 0.0 0.17
69 2014-9-7 80 68 92 64 84 50 103 1884 1949 0.0 0.0 0.0
70 2014-9-8 80 71 88 64 84 47 103 1901 1984 0.01 0.0 0.19
71 2014-9-9 80 68 91 64 84 48 102 1884 1956 0.0 0.01 0.01
72 2014-9-10 76 64 87 64 84 52 103 1893 1983 0.0 0.0 1.74
73 2014-9-11 78 67 89 64 84 48 101 1901 1983 0.0 0.01 0.33
74 2014-9-12 80 68 91 64 84 48 102 1884 1971 0.0 0.01 0.13
75 2014-9-13 82 69 94 64 84 48 106 1884 1971 0.0 0.0 0.07
76 2014-9-14 85 71 98 63 84 48 100 1898 2012 0.0 0.01 0.04
77 2014-9-15 84 73 94 63 83 49 103 1895 2012 0.0 0.01 0.03
78 2014-9-16 90 76 103 63 83 48 103 1884 1909 0.0 0.01 0.07
79 2014-9-17 84 72 96 63 83 46 108 1884 1913 0.0 0.01 0.42
80 2014-9-18 74 67 81 63 83 48 103 1884 1939 0.0 0.01 1.39
81 2014-9-19 75 67 82 63 83 49 104 1907 1939 0.0 0.01 0.27
82 2014-9-20 72 66 78 63 83 49 107 1900 1939 0.0 0.01 0.29
83 2014-9-21 72 65 79 63 82 47 108 1880 1885 0.0 0.01 0.15
84 2014-9-22 72 63 80 63 82 48 104 1895 1883 0.0 0.02 0.4
85 2014-9-23 74 63 84 62 82 44 104 1880 1978 0.0 0.01 0.28
86 2014-9-24 75 62 88 62 82 45 106 1880 1978 0.0 0.01 1.95
87 2014-9-25 76 67 85 62 82 48 107 1879 1978 0.0 0.01 3.96
88 2014-9-26 74 65 83 62 82 48 109 1893 1963 0.0 0.01 0.24
89 2014-9-27 70 63 77 62 81 46 113 1901 2010 0.0 0.02 0.68
90 2014-9-28 72 64 79 62 81 49 106 1901 1963 0.0 0.01 0.74
91 2014-9-29 70 61 78 62 81 44 102 1880 1999 0.0 0.01 0.49
92 2014-9-30 75 64 85 62 81 48 105 1886 1906 0.0 0.02 1.58
93 2014-10-1 73 64 82 61 81 49 100 1901 1991 0.0 0.01 0.74
94 2014-10-2 81 64 98 61 81 44 101 1884 1995 0.0 0.02 0.53
95 2014-10-3 83 67 98 61 80 44 108 1884 1987 0.0 0.02 0.37
96 2014-10-4 81 65 97 61 80 44 108 1884 1987 0.0 0.01 0.24
97 2014-10-5 80 65 95 61 80 46 101 1884 1971 0.0 0.02 1.15
98 2014-10-6 78 64 92 61 80 44 102 1881 1971 0.0 0.02 0.3
99 2014-10-7 79 64 93 60 80 43 98 1884 1971 0.0 0.02 0.17
100 2014-10-8 75 63 87 60 80 43 100 1881 1994 0.0 0.02 0.42

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CREATE TABLE "us-weather-history/KCQT" (
"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
)
Powered by Datasette · Query took 88.213ms · Data license: CC Attribution 4.0 License · Data source: fivethirtyeight/data on GitHub