Oslo AirBNB Data

Simple insights about Airbnb accommodations in Oslo

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photo credit: www.visitoslo.com

Data set Description

Listing columns type:
id int64
name object
host_id int64
host_name object
neighbourhood_group float64
neighbourhood object
latitude float64
longitude float64
room_type object
price int64
minimum_nights int64
number_of_reviews int64
last_review object
reviews_per_month float64
calculated_host_listings_count int64
availability_365 int64
Encoded dataframe types:
id int64
host_id int64
neighbourhood int8
room_type int8
price int64
minimum_nights int64

Q1: How are advertised accommodations distributed across neighborhoods/districts in Oslo?

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Fig. 1 Accommodations shares by neighborhood
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Fig. 2 Source: https://www.ssb.no/en/befolkning/statistikker/fobbolig/hvert-10-aar/2013-02-26

Q2: What are accommodation types mostly advertised at Airbnb in Oslo?

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Fig.3 The distribution of the listings per type

Q3: How do accommodation prices look like?

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Fig.4 Raw prices data scatter plot
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Fig. 5 Prices data scatter plot after omitting outliers
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Fig. 6 Prices distribution
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Fig. 7 Average prices by room_type
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Fig. 8 Average prices by neighborhood

Q4: What price we can suggest to a new accommodation owner who wants to post an advertisement in Airbnb?

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Fig.9 Correlation matrix
neighbourhood        room_type
0 Frogner Entire home/apt
1 Østensjø Entire home/apt
2 Grünerløkka Private room
3 Sagene Shared room
4 Frogner Shared room
neighbourhood        room_type  price_pred
0 Frogner Entire home/apt 1184
1 Østensjø Entire home/apt 1174
2 Grünerløkka Private room 630
3 Sagene Shared room 348
4 Frogner Shared room 360

Conclusion

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