Datasets:
DAY_OF_YEAR
float64 1
366
| PRECIPITATION
float64 0
4.53
| LAGGED_PRECIPITATION
float64 0
8.18
| AVG_WIND_SPEED
float64 1.79
26.2
| MIN_TEMP
float64 33
77
| MAX_TEMP
float64 50
106
|
---|---|---|---|---|---|
1 | 0 | 0 | 4.7 | 51 | 79 |
2 | 0 | 0 | 5.59 | 46 | 71 |
3 | 0 | 0 | 5.37 | 47 | 70 |
4 | 0 | 0 | 4.7 | 45 | 76 |
5 | 0 | 0 | 5.14 | 49 | 74 |
6 | 0 | 0 | 7.38 | 49 | 65 |
7 | 0 | 0 | 5.82 | 54 | 59 |
8 | 0 | 0 | 3.36 | 55 | 59 |
9 | 0 | 0 | 6.71 | 54 | 61 |
10 | 0 | 0 | 4.7 | 47 | 70 |
11 | 0 | 0 | 5.82 | 46 | 68 |
12 | 0 | 0 | 5.14 | 47 | 69 |
13 | 0 | 0 | 6.93 | 48 | 62 |
14 | 0 | 0 | 6.04 | 48 | 59 |
15 | 0 | 0 | 6.71 | 43 | 59 |
16 | 0.39 | 0.39 | 6.71 | 45 | 55 |
17 | 0 | 0.39 | 5.59 | 41 | 63 |
18 | 0 | 0.39 | 5.59 | 44 | 61 |
19 | 0 | 0.39 | 4.92 | 47 | 60 |
20 | 0 | 0.39 | 5.59 | 44 | 70 |
21 | 0 | 0.39 | 5.82 | 53 | 64 |
22 | 0 | 0.39 | 6.71 | 45 | 62 |
23 | 0 | 0 | 5.59 | 45 | 66 |
24 | 0 | 0 | 4.25 | 48 | 70 |
25 | 0 | 0 | 6.04 | 51 | 74 |
26 | 0 | 0 | 13.65 | 48 | 73 |
27 | 0 | 0 | 8.5 | 57 | 79 |
28 | 0 | 0 | 5.59 | 50 | 76 |
29 | 0 | 0 | 5.59 | 51 | 78 |
30 | 0 | 0 | 5.82 | 54 | 78 |
31 | 0 | 0 | 5.14 | 54 | 73 |
32 | 0 | 0 | 7.61 | 53 | 62 |
33 | 0 | 0 | 6.71 | 51 | 62 |
34 | 0 | 0 | 5.82 | 52 | 72 |
35 | 0 | 0 | 6.49 | 53 | 67 |
36 | 0 | 0 | 7.16 | 48 | 65 |
37 | 0 | 0 | 5.37 | 49 | 73 |
38 | 0 | 0 | 5.82 | 49 | 75 |
39 | 0 | 0 | 5.37 | 48 | 68 |
40 | 0 | 0 | 6.71 | 52 | 62 |
41 | 0.01 | 0.01 | 11.18 | 51 | 65 |
42 | 0 | 0.01 | 7.61 | 49 | 65 |
43 | 0 | 0.01 | 5.59 | 48 | 67 |
44 | 0 | 0.01 | 7.61 | 50 | 66 |
45 | 0 | 0.01 | 10.74 | 53 | 65 |
46 | 0 | 0.01 | 6.26 | 48 | 65 |
47 | 0 | 0.01 | 17.67 | 52 | 62 |
48 | 0 | 0 | 15.21 | 52 | 64 |
49 | 0 | 0 | 6.49 | 45 | 68 |
50 | 0 | 0 | 6.26 | 44 | 72 |
51 | 0 | 0 | 5.82 | 43 | 72 |
52 | 0 | 0 | 8.28 | 46 | 68 |
53 | 0 | 0 | 7.83 | 52 | 65 |
54 | 0 | 0 | 7.38 | 46 | 71 |
55 | 0 | 0 | 6.71 | 47 | 63 |
56 | 0 | 0 | 15.43 | 52 | 68 |
57 | 0 | 0 | 5.82 | 47 | 73 |
58 | 0 | 0 | 8.05 | 50 | 79 |
59 | 0 | 0 | 7.83 | 51 | 72 |
60 | 0 | 0 | 6.71 | 49 | 68 |
61 | 0 | 0 | 7.38 | 51 | 65 |
62 | 0 | 0 | 6.26 | 53 | 64 |
63 | 0 | 0 | 8.05 | 54 | 69 |
64 | 0 | 0 | 6.26 | 56 | 66 |
65 | 0 | 0 | 7.61 | 50 | 70 |
66 | 0 | 0 | 7.61 | 49 | 75 |
67 | 0 | 0 | 7.38 | 51 | 70 |
68 | 0 | 0 | 8.95 | 51 | 66 |
69 | 0 | 0 | 6.49 | 54 | 65 |
70 | 0 | 0 | 7.61 | 52 | 72 |
71 | 0 | 0 | 7.83 | 55 | 66 |
72 | 0 | 0 | 9.17 | 54 | 68 |
73 | 0 | 0 | 7.83 | 53 | 67 |
74 | 0.14 | 0.14 | 12.3 | 56 | 65 |
75 | 0 | 0.14 | 10.29 | 52 | 64 |
76 | 0 | 0.14 | 8.5 | 52 | 66 |
77 | 0 | 0.14 | 9.17 | 50 | 72 |
78 | 0 | 0.14 | 7.61 | 56 | 77 |
79 | 0 | 0.14 | 6.26 | 53 | 78 |
80 | 0 | 0.14 | 6.71 | 58 | 76 |
81 | 0 | 0 | 7.16 | 56 | 66 |
82 | 0 | 0 | 8.05 | 54 | 69 |
83 | 0 | 0 | 7.38 | 54 | 77 |
84 | 0 | 0 | 6.71 | 53 | 69 |
85 | 0 | 0 | 7.38 | 54 | 68 |
86 | 0 | 0 | 5.82 | 57 | 62 |
87 | 0 | 0 | 8.5 | 53 | 76 |
88 | 0 | 0 | 8.72 | 56 | 78 |
89 | 0 | 0 | 11.41 | 53 | 71 |
90 | 0 | 0 | 8.05 | 50 | 68 |
91 | 0 | 0 | 15.66 | 52 | 63 |
92 | 0 | 0 | 10.07 | 48 | 63 |
93 | 0 | 0 | 8.05 | 50 | 66 |
94 | 0 | 0 | 7.83 | 50 | 66 |
95 | 0 | 0 | 6.26 | 54 | 63 |
96 | 0 | 0 | 8.28 | 55 | 67 |
97 | 0.87 | 0.87 | 10.51 | 53 | 66 |
98 | 0 | 0.87 | 7.38 | 55 | 70 |
99 | 0 | 0.87 | 6.93 | 55 | 65 |
100 | 0 | 0.87 | 8.72 | 53 | 69 |
📦 Dataset Card: CA_Weather_Fire_Dataset_Cleaned
Dataset Summary
This dataset contains cleaned and preprocessed weather and fire incident data for California (1984–2025). The original dataset, California Weather and Fire Prediction Dataset (1984–2025) with Engineered Features, includes features such as temperature, humidity, wind speed, fire occurrence, and seasonal indicators. From the Original Dataset, I changed the data types to floats, rearranged the columns, removed multiple columns, and eliminated entries that had NaNs. This dataset focuses on predicting the 'MAX_TEMP' column given 5 features.
Original Features
- DATE (string): The date of the observation.
- DAY_OF_YEAR (float): The numeric day within the year (1–365/366).
- MONTH (float): The calendar month of the observation (1–12).
- YEAR (float): The year of the observation.
- SEASON (float): Encoded season (1.0 = Winter, 2.0 = Spring, 3.0 = Summer, 4.0 = Fall)
- PRECIPITATION (float): Daily precipitation in inches.
- LAGGED_PRECIPITATION (float): Cumulative precipitation over the preceding 7 days, reflecting recent moisture conditions.
- AVG_WIND_SPEED (float): Average daily wind speed in mph.
- LAGGED_AVG_WIND_SPEED (float): Average wind speed over the preceding 7 days, indicating sustained wind patterns.
- WIND_TEMP_RATIO (float): The ratio of average wind speed to maximum temperature, capturing wind-temperature dynamics.
- MIN_TEMP (float): Minimum daily temperature in degrees Fahrenheit.
- TEMP_RANGE (float): The difference between maximum and minimum temperatures, indicating daily temperature variability.
- FIRE_START_DAY (float): Indicator of fire occurrence (1.0 for fire, 0.0 for no fire)
- MAX_TEMP (float): Maximum daily temperature in degrees Fahrenheit.
Cleaned Features
- DAY_OF_YEAR (float): The numeric day within the year (1–365/366).
- PRECIPITATION (float): Daily precipitation in inches.
- LAGGED_PRECIPITATION (float): Cumulative precipitation over the preceding 7 days, reflecting recent moisture conditions.
- AVG_WIND_SPEED (float): Average daily wind speed in mph.
- MIN_TEMP (float): Minimum daily temperature in degrees Fahrenheit.
- MAX_TEMP (float): Maximum daily temperature in degrees Fahrenheit.
Source and License
This dataset is derived from publicly available data licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
Attribution:
This dataset includes data sourced from California Weather and Fire Prediction Dataset (1984–2025) with Engineered Features, which is licensed under the Creative Commons Attribution 4.0 International License. You are free to share and adapt the material for any purpose, even commercially, as long as appropriate credit is given, a link to the license is provided, and any changes made are indicated.
Intended Uses
- Wildfire prediction models
- Environmental data analysis
- Educational and research purposes
How to Use
from datasets import load_dataset
dataset = load_dataset("MaxPrestige/CA_Weather_Fire_Dataset_Cleaned")
Citation
If you use this dataset in your research or application, please cite the original source and this dataset card.
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