mieszkania5/SysInf.ipynb

!git clone git://gonito.net/mieszkania5

fatal: destination path 'mieszkania5' already exists and is not an empty directory.

import pandas as pd

train = r'j:\Desktop\SysInf\mieszkania5\train\train.tsv'
train

'j:\\\\Desktop\\\\SysInf\\\\mieszkania5\\\\train\\\\train.tsv'

data=pd.read_csv(train, sep='\t', header=None)

data.columns

Index([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,
       18, 19, 20, 21, 22, 23, 24, 25],
      dtype='int64')

x_train = data[[0,6,8,19]]

x_train

	0	6	8	19
0	309000.0	2	43.44	NaN
1	314900.0	2	42.60	NaN
2	249000.0	2	44.30	1960.0
3	419000.0	4	88	NaN
4	499000.0	3	77	NaN
...	...	...	...	...
2542	507600.0	4	94	1914.0
2543	342400.0	2	53.50	1999.0
2544	335000.0	3	55.25	1910.0
2545	260000.0	3	62	1930.0
2546	1990000.0	więcej niż 10	392	NaN

2547 rows × 4 columns

x_train = x_train.dropna()

x_train = x_train.replace( "więcej niż 10", '11')

x_train = x_train[(x_train[19] >= 1800) | (x_train[19] <= 2023)]

x_train = x_train.rename(columns = {0:"cena", 6:"pokoje", 8:"metraz", 19:"rok"})

x_train = x_train[x_train["metraz"] != '6 909']

x_train["pokoje"] = x_train["pokoje"].astype(float)
x_train["metraz"] = x_train["metraz"].astype(float)

x_train

	cena	pokoje	metraz	rok
2	249000.0	2.0	44.30	1960.0
6	449000.0	4.0	92.00	1930.0
7	389000.0	3.0	63.60	1985.0
9	260000.0	3.0	44.20	1970.0
10	330682.0	3.0	48.99	2019.0
...	...	...	...	...
2541	383680.0	3.0	70.40	2016.0
2542	507600.0	4.0	94.00	1914.0
2543	342400.0	2.0	53.50	1999.0
2544	335000.0	3.0	55.25	1910.0
2545	260000.0	3.0	62.00	1930.0

1767 rows × 4 columns

from sklearn.linear_model import LinearRegression

x = x_train[["pokoje", "metraz", "rok"]]

y = x_train[["cena"]]

model = LinearRegression()

model.fit(x,y)

LinearRegression()

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LinearRegression

LinearRegression()

import matplotlib.pyplot as plt

model.coef_

array([[-3.54305400e+04,  7.47165498e+03, -2.77294899e+00]])

plt.plot(x["pokoje"],y, 'o')
plt.plot(x["pokoje"],model.predict(x), '--')

[<matplotlib.lines.Line2D at 0x1ea4fa86bc0>]

plt.plot(x["rok"],y, 'o')
plt.plot(x["rok"],model.predict(x), '-')

[<matplotlib.lines.Line2D at 0x1ea50bcb940>]

plt.plot(x["metraz"],y, 'o')
plt.plot(x["metraz"],model.predict(x), 'o')

[<matplotlib.lines.Line2D at 0x1ea50b570a0>]

model.predict(x)

array([[330020.67101959],
       [615640.72224431],
       [438723.7484912 ],
       ...,
       [398651.75187026],
       [376543.40054119],
       [426921.61270958]])