Introduction to data and Line Plot

This is the second blog in the series of matplotlib and in the previous blog we have seen why we need data visualization, the architecture of matplotlib. If you want to go to http://blog.robofied.com/introduction-matplotlib/.

Introduction to Data

In this series, we are going to use data which contains information about cars/automobiles in order to predict prices for cars. So, will learn EDA with this data set by trying different graphs/visualization. Dataset can be downloaded from here -: LINK. Originally data is taken from here.

Data Description

This data set consists of three types of entities: (a) the specification of an auto in terms of various characteristics, (b) its assigned insurance risk rating, (c) its normalized losses in use as compared to other cars. The second rating corresponds to the degree to which the auto is riskier than its price indicates. Cars are initially assigned a risk factor symbol associated with its price. Then, if it is riskier (or less), this symbol is adjusted by moving it up (or down) the scale. Actuaries call this process “symboling”. A value of +3 indicates that the auto is risky, -3 that it is probably pretty safe.

The third factor is the relative average loss payment per insured vehicle year. This value is normalized for all autos within a particular size classification (two-door small, station wagons, sports/specialty, etc…), and represents the average loss per car per year.

Note: Several of the attributes in the database could be used as a “class” attribute.

Attribute: Attribute Range

1. symboling: -3, -2, -1, 0, 1, 2, 3.
2. normalized-losses: continuous from 65 to 256.
3. make: alfa-Romero, Audi, BMW, Chevrolet, Dodge, Honda,  Isuzu, Jaguar, Mazda, Mercedes-Benz, Mercury, Mitsubishi, Nissan, Peugeot, Plymouth, Porsche, Renault, Saab, Subaru, Toyota, Volkswagen, Volvo
4. fuel-type: diesel, gas.
5. aspiration: std, turbo(aspirated engine).
6. num-of-doors: four, two.
7. body-style: hardtop, wagon, sedan, hatchback, convertible.
8. drive-wheels: 4wd, fwd, rwd.
9. engine-location: front, rear.
10. wheel-base: continuous from 86.6 120.9(distance between centers of the front and rear wheel).
11. length: continuous from 141.1 to 208.1.
12. width: continuous from 60.3 to 72.3.
13. height: continuous from 47.8 to 59.8.
14. curb-weight: continuous from 1488 to 4066(total mass).
15. engine-type: dohc, dohcv, l, ohc, ohcf, ohcv, rotor.
16. num-of-cylinders: eight, five, four, six, three, twelve, two.
17. engine-size: continuous from 61 to 326.
18. fuel-system: 1bbl, 2bbl, 4bbl, idi, mfi, mpfi, spdi, spfi.
19. bore: continuous from 2.54 to 3.94(part of engine, diameter or radius of cylindrical shape part in the engine).
20. stroke: continuous from 2.07 to 4.17(A stroke refers to the full travel of the piston along the cylinder, in either direction)
21. compression-ratio: continuous from 7 to 23.
22. horsepower: continuous from 48 to 288.
23. peak-rpm: continuous from 4150 to 6600.
24. city mpg: continuous from 13 to 49(mileage in a city).
25. highway-mpg: continuous from 16 to 54(mileage at highway).
26. price: continuous from 5118 to 45400.

These are variable but will do EDA and understand how they are related to each other and affecting the price of cars as well.

 

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