Data
mauna-loa-atmospheric-co2

mauna-loa-atmospheric-co2

active ARFF Public Domain (CC0) Visibility: public Uploaded 30-08-2018 by Max Copeland
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Weekly carbon-dioxide concentration averages derived from continuous air samples for the Mauna Loa Observatory, Hawaii, U.S.A.

These weekly averages are ultimately based on measurements of 4 air samples per hour taken atop intake lines on several towers during steady periods of CO2 concentration of not less than 6 hours per day; if no such periods are available on a given day, then no data are used for that day. The _Weight_ column gives the number of days used in each weekly average. _Flag_ codes are explained in the NDP writeup, available electronically from the [home page](http://cdiac.ess-dive.lbl.gov/ftp/trends/co2/sio-keel-flask/maunaloa_c.dat) of this data set. CO2 concentrations are in terms of the 1999 calibration scale (Keeling et al., 2002) available electronically from the references in the NDP writeup which can be accessed from the home page of this data set.

### Feature Descriptions _co2_: average co2 concentration in ppvm
_year_: year of concentration measurement
_month_: month of concentration measurement
_day_: day of month of concentration measurement
_weight_: number of days used in each weekly average
_flag_: flag code
_station_: station code

Author: Carbon Dioxide Research Group, Scripps Institution of Oceanography, University of California-San Diego, La Jolla, California, USA 92023-0444
Source: [original](http://cdiac.ess-dive.lbl.gov/ftp/trends/co2/sio-keel-flask/maunaloa_c.dat) - September 2004

7 features

co2 (target)numeric581 unique values
0 missing
yearnumeric44 unique values
0 missing
monthnumeric12 unique values
0 missing
daynumeric31 unique values
0 missing
weightnumeric7 unique values
0 missing
flagnumeric1 unique values
0 missing
stationnominal1 unique values
0 missing

62 properties

2225
Number of instances (rows) of the dataset.
7
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
6
Number of numeric attributes.
1
Number of nominal attributes.
-0.63
First quartile of skewness among attributes of the numeric type.
391.38
Mean of means among attributes of the numeric type.
1.04
First quartile of standard deviation of attributes of the numeric type.
0.61
Average class difference between consecutive instances.
Average mutual information between the nominal attributes and the target attribute.
Second quartile (Median) of entropy among attributes.
Entropy of the target attribute values.
An estimate of the amount of irrelevant information in the attributes regarding the class. Equals (MeanAttributeEntropy - MeanMutualInformation) divided by MeanMutualInformation.
-1.19
Second quartile (Median) of kurtosis among attributes of the numeric type.
0
Number of attributes divided by the number of instances.
1
Average number of distinct values among the attributes of the nominal type.
11.15
Second quartile (Median) of means among attributes of the numeric type.
Number of attributes needed to optimally describe the class (under the assumption of independence among attributes). Equals ClassEntropy divided by MeanMutualInformation.
-0.21
Mean skewness among attributes of the numeric type.
Second quartile (Median) of mutual information between the nominal attributes and the target attribute.
Percentage of instances belonging to the most frequent class.
7.19
Mean standard deviation of attributes of the numeric type.
-0.03
Second quartile (Median) of skewness among attributes of the numeric type.
Number of instances belonging to the most frequent class.
Minimal entropy among attributes.
0
Percentage of binary attributes.
6.12
Second quartile (Median) of standard deviation of attributes of the numeric type.
Maximum entropy among attributes.
-1.21
Minimum kurtosis among attributes of the numeric type.
0
Percentage of instances having missing values.
Third quartile of entropy among attributes.
1.03
Maximum kurtosis among attributes of the numeric type.
0
Minimum of means among attributes of the numeric type.
0
Percentage of missing values.
-0.07
Third quartile of kurtosis among attributes of the numeric type.
1980.03
Maximum of means among attributes of the numeric type.
Minimal mutual information between the nominal attributes and the target attribute.
85.71
Percentage of numeric attributes.
750.11
Third quartile of means among attributes of the numeric type.
Maximum mutual information between the nominal attributes and the target attribute.
1
The minimal number of distinct values among attributes of the nominal type.
14.29
Percentage of nominal attributes.
Third quartile of mutual information between the nominal attributes and the target attribute.
1
The maximum number of distinct values among attributes of the nominal type.
-1.22
Minimum skewness among attributes of the numeric type.
First quartile of entropy among attributes.
0.11
Third quartile of skewness among attributes of the numeric type.
0.22
Maximum skewness among attributes of the numeric type.
0
Minimum standard deviation of attributes of the numeric type.
-1.2
First quartile of kurtosis among attributes of the numeric type.
13.62
Third quartile of standard deviation of attributes of the numeric type.
17
Maximum standard deviation of attributes of the numeric type.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
4.36
First quartile of means among attributes of the numeric type.
0
Standard deviation of the number of distinct values among attributes of the nominal type.
Average entropy of the attributes.
0
Number of binary attributes.
First quartile of mutual information between the nominal attributes and the target attribute.
-0.75
Mean kurtosis among attributes of the numeric type.

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