OpenML
Xeno-Canto-Birds-from-India

Xeno-Canto-Birds-from-India

active ARFF CC0: Public Domain Visibility: public Uploaded 24-03-2022 by Elif Ceren Gok
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Context https://www.kaggle.com/c/birdsong-recognition Content This is information captured about birds recording from India Acknowledgements We wouldn't be here without the help of many contributors to https://www.xeno-canto.org/: https://www.xeno-canto.org/contributors Inspiration You can use this data to start exploring the amazing landscape of birds recording. Based on frequency of birds recording in different areas, one can assess the species migration, species evolution as well as impact of various factors like air pollution (birds are an early indicator of pollution). Find interesting facts about the birds distribution and characteristics from the beautiful and rich in diversity Indian subcontinent.

26 features

idnumeric13654 unique values
0 missing
genstring405 unique values
0 missing
spstring791 unique values
0 missing
sspstring493 unique values
11919 missing
enstring984 unique values
0 missing
recstring476 unique values
0 missing
cntstring1 unique values
0 missing
locstring1994 unique values
539 missing
latnumeric2527 unique values
824 missing
lngnumeric2504 unique values
824 missing
altstring255 unique values
3054 missing
typestring451 unique values
39 missing
urlstring13654 unique values
0 missing
filestring13120 unique values
534 missing
file-namestring13112 unique values
534 missing
sonostring13654 unique values
0 missing
licstring7 unique values
0 missing
qstring6 unique values
0 missing
lengthstring255 unique values
0 missing
timestring1328 unique values
458 missing
datestring2685 unique values
0 missing
uploadedstring1799 unique values
0 missing
alsostring959 unique values
0 missing
rmkstring4645 unique values
8138 missing
bird-seenstring3 unique values
0 missing
playback-usedstring3 unique values
0 missing

19 properties

13654
Number of instances (rows) of the dataset.
26
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
26863
Number of missing values in the dataset.
12853
Number of instances with at least one value missing.
3
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
11.54
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
94.13
Percentage of instances having missing values.
Average class difference between consecutive instances.
7.57
Percentage of missing values.

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