Path: blob/master/05_Merge/Auto_MPG/Solutions.ipynb
548 views
Kernel: Python [default]
MPG Cars
Check out Cars Exercises Video Tutorial to watch a data scientist go through the exercises
Introduction:
The following exercise utilizes data from UC Irvine Machine Learning Repository
Step 1. Import the necessary libraries
In [24]:
Step 3. Assign each to a to a variable called cars1 and cars2
In [2]:
Out[2]:
mpg cylinders displacement horsepower weight acceleration model \
0 18.0 8 307 130 3504 12.0 70
1 15.0 8 350 165 3693 11.5 70
2 18.0 8 318 150 3436 11.0 70
3 16.0 8 304 150 3433 12.0 70
4 17.0 8 302 140 3449 10.5 70
origin car Unnamed: 9 Unnamed: 10 Unnamed: 11 \
0 1 chevrolet chevelle malibu NaN NaN NaN
1 1 buick skylark 320 NaN NaN NaN
2 1 plymouth satellite NaN NaN NaN
3 1 amc rebel sst NaN NaN NaN
4 1 ford torino NaN NaN NaN
Unnamed: 12 Unnamed: 13
0 NaN NaN
1 NaN NaN
2 NaN NaN
3 NaN NaN
4 NaN NaN
mpg cylinders displacement horsepower weight acceleration model \
0 33.0 4 91 53 1795 17.4 76
1 20.0 6 225 100 3651 17.7 76
2 18.0 6 250 78 3574 21.0 76
3 18.5 6 250 110 3645 16.2 76
4 17.5 6 258 95 3193 17.8 76
origin car
0 3 honda civic
1 1 dodge aspen se
2 1 ford granada ghia
3 1 pontiac ventura sj
4 1 amc pacer d/l
Step 4. Oops, it seems our first dataset has some unnamed blank columns, fix cars1
In [12]:
Out[12]:
Step 5. What is the number of observations in each dataset?
In [14]:
Out[14]:
(198, 9)
(200, 9)
Step 6. Join cars1 and cars2 into a single DataFrame called cars
In [23]:
Out[23]:
Step 7. Oops, there is a column missing, called owners. Create a random number Series from 15,000 to 73,000.
In [33]:
Out[33]:
array([29487, 25680, 65268, 31827, 69215, 72602, 52693, 58440, 16183,
45014, 32318, 72942, 62163, 35951, 57625, 59355, 36533, 67048,
58159, 69743, 25146, 22755, 44966, 46792, 56553, 65013, 55908,
69563, 22030, 59561, 15593, 52998, 54795, 16169, 24809, 35580,
46590, 38792, 43099, 37166, 21390, 56496, 68606, 21110, 56334,
45477, 51961, 27625, 51176, 30796, 61809, 65450, 67375, 23342,
27499, 50585, 57302, 56191, 60281, 32865, 58605, 66374, 15315,
31791, 28670, 38796, 69214, 41055, 32353, 31574, 65799, 42998,
72785, 18415, 31977, 29812, 65439, 21161, 60871, 67151, 22179,
32821, 55392, 34586, 67937, 31646, 66397, 35258, 63815, 71291,
51130, 27684, 49648, 52691, 50681, 68185, 32635, 51553, 28970,
19112, 26035, 67666, 55471, 51477, 62055, 53003, 41265, 18565,
48851, 48673, 45832, 67891, 57638, 29240, 41236, 16950, 31449,
50528, 22397, 15876, 26414, 16736, 23896, 46104, 17583, 65951,
38538, 31443, 19299, 46095, 31239, 19290, 38051, 68575, 61755,
22560, 34460, 35395, 34608, 56906, 44895, 48429, 20900, 49770,
50513, 59402, 26893, 37233, 19036, 20523, 18765, 46333, 42831,
53698, 25218, 63106, 16928, 34901, 43674, 65453, 54428, 68502,
19043, 20325, 45039, 29466, 49672, 67972, 30547, 22522, 69354,
40489, 72887, 15724, 51442, 65182, 64555, 42138, 72988, 20861,
67898, 20768, 36415, 47480, 16820, 48739, 62610, 43473, 23002,
43488, 62581, 37724, 63019, 44912, 35595, 59188, 51814, 65283,
53479, 27660, 38237, 22957, 47870, 15533, 41944, 51830, 56676,
57481, 48529, 72220, 66675, 50099, 30585, 25436, 49195, 26050,
24899, 37213, 25870, 67447, 23808, 71275, 67572, 18545, 43553,
54858, 23077, 33705, 31282, 26298, 23742, 36110, 51491, 18019,
60655, 27453, 35563, 63627, 35315, 56717, 59281, 55634, 18415,
59570, 47320, 20110, 18425, 19352, 18032, 31816, 28573, 66030,
54723, 21592, 37160, 59518, 35629, 47619, 52359, 34566, 64932,
24072, 39445, 31203, 63975, 62041, 70175, 51029, 32058, 19428,
65553, 50799, 48190, 68061, 68201, 53389, 15901, 44585, 54723,
30446, 63716, 57488, 67134, 22033, 53694, 40002, 24854, 59747,
59827, 53378, 53196, 68686, 20784, 28181, 33044, 41694, 39857,
57296, 69021, 17359, 29794, 22515, 55877, 22806, 50027, 56787,
50844, 17420, 65259, 19141, 40204, 19530, 30116, 34973, 15641,
53492, 59574, 59082, 64400, 70163, 43058, 69696, 67996, 26158,
32936, 45461, 47390, 32368, 15400, 40895, 16572, 31776, 62121,
56704, 39335, 27716, 52565, 50831, 45049, 25173, 25018, 18606,
71177, 66288, 46754, 68175, 35829, 24959, 54792, 19059, 29092,
58736, 62938, 44733, 17884, 33905, 33965, 24641, 52257, 28178,
29515, 37703, 56036, 51556, 23590, 61888, 70224, 53730, 41328,
16501, 30360, 54106, 29101, 35631, 56173, 30424, 46887, 23657,
17723, 71709, 45270, 30380, 27779, 33774, 36379, 47127, 63625,
16750, 65740, 53802, 40995, 37487, 42791, 21825, 69344, 63210,
15982, 20259])
Step 8. Add the column owners to cars
In [34]:
Out[34]: