Data
Istanbul-Airbnb-Dataset

Istanbul-Airbnb-Dataset

active ARFF CC0: Public Domain Visibility: public Uploaded 24-03-2022 by Dustin Carrion
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Context This dataset collected from airbnb. It is collected to see how airbnb is used in Turkey Istanbul. Content There are 16 columns which shows the latitude, longitude etc. It also shows the price. So, a regression problem such as finding the price of an house can be applied to this dataset. To see an example you can check my notebook from airbnb newyork dataset

16 features

idnumeric23728 unique values
0 missing
namestring22563 unique values
75 missing
host_idnumeric14450 unique values
0 missing
host_namestring4816 unique values
49 missing
neighbourhood_groupnumeric0 unique values
23728 missing
neighbourhoodstring39 unique values
0 missing
latitudenumeric10858 unique values
0 missing
longitudenumeric12458 unique values
0 missing
room_typestring4 unique values
0 missing
pricenumeric501 unique values
0 missing
minimum_nightsnumeric65 unique values
0 missing
number_of_reviewsnumeric230 unique values
0 missing
last_reviewstring1424 unique values
12375 missing
reviews_per_monthnumeric473 unique values
12375 missing
calculated_host_listings_countnumeric35 unique values
0 missing
availability_365numeric353 unique values
0 missing

19 properties

23728
Number of instances (rows) of the dataset.
16
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
48602
Number of missing values in the dataset.
23728
Number of instances with at least one value missing.
11
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
68.75
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.
100
Percentage of instances having missing values.
Average class difference between consecutive instances.
12.8
Percentage of missing values.

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