machine-learning-1-practical

In [4]:

from IPython.display import Image
from IPython.core.display import HTML 
from IPython.display import IFrame

In [21]:

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import os

In [22]:

pwd

Out[22]:

'F:\\python for data science and machine learning\\machine-learning-1'

In [41]:

os.listdir('F:/python for data science and machine learning/machine-learning-1')

Out[41]:

['.ipynb_checkpoints',
 'death .csv',
 'machine-learning-1-practical.ipynb',
 'screenshots']

In [48]:

data = pd.read_csv('death .csv')   # attemtion death ke baad file me space tha phir csv isliye read nhi ho rhi thi
data.head()

Out[48]:

	County	FIPS	Met Objective of 45.5? (1)	Age-Adjusted Death Rate	Lower 95% Confidence Interval for Death Rate	Upper 95% Confidence Interval for Death Rate	Average Deaths per Year	Recent Trend (2)	Recent 5-Year Trend (2) in Death Rates	Lower 95% Confidence Interval for Trend	Upper 95% Confidence Interval for Trend
0	United States	0	No	46	45.9	46.1	157,376	falling	-2.4	-2.6	-2.2
1	Perry County, Kentucky	21193	No	125.6	108.9	144.2	43	stable	-0.6	-2.7	1.6
2	Powell County, Kentucky	21197	No	125.3	100.2	155.1	18	stable	1.7	0	3.4
3	North Slope Borough, Alaska	2185	No	124.9	73	194.7	5	**	**	**	**
4	Owsley County, Kentucky	21189	No	118.5	83.1	165.5	8	stable	2.2	-0.4	4.8

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