diff --git a/notebooks/Block_0/Exercise Sheet - Basics Numpy.ipynb b/notebooks/Block_0/Exercise Sheet - Basics Numpy.ipynb
index 1448f33090fe73ef340591659ef141bcfa3809f3..8dff11b44153eca7940c63d131916d238016b355 100644
--- a/notebooks/Block_0/Exercise Sheet - Basics Numpy.ipynb
+++ b/notebooks/Block_0/Exercise Sheet - Basics Numpy.ipynb
@@ -717,21 +717,542 @@
"metadata": {},
"source": [
"# Problem 4: Fuel Consumption\n",
- "In this exercise, you will analyse a dataset containing information on Fuel consumption of cars in the eighties. The data contains 3 columns, the weight of the car in Pounds(1 Pound = 0.454 kg), the range in Miles per Gallon(1 mile=1.61 km; 1 gallon=3.79 l), and the type of car. Download the dataset and save it somewhere practically, possibly in the same folder as this notebook."
+ "In this exercise, you will analyse a dataset containing information on Fuel consumption of cars in the eighties. The data contains 3 columns, the weight of the car in Pounds(1 Pound = 0.454 kg), the range in Miles per Gallon(1 mile=1.61 km; 1 gallon=3.79 l), and the type of car. Download the dataset and save it somewhere practical, possibly in the same folder as this notebook."
]
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 44,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
+ " vertical-align: middle;\n",
+ " }\n",
+ "\n",
+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
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+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>X</th>\n",
+ " <th>weight</th>\n",
+ " <th>mpg</th>\n",
+ " <th>type</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
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+ " <td>Small</td>\n",
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+ " <td>4</td>\n",
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+ " <td>32</td>\n",
+ " <td>Small</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>5</td>\n",
+ " <td>2440</td>\n",
+ " <td>32</td>\n",
+ " <td>Small</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>5</th>\n",
+ " <td>6</td>\n",
+ " <td>2285</td>\n",
+ " <td>26</td>\n",
+ " <td>Small</td>\n",
+ " </tr>\n",
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+ " <th>6</th>\n",
+ " <td>7</td>\n",
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+ " <td>8</td>\n",
+ " <td>2350</td>\n",
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+ " <td>Small</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>8</th>\n",
+ " <td>9</td>\n",
+ " <td>2295</td>\n",
+ " <td>25</td>\n",
+ " <td>Small</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>9</th>\n",
+ " <td>10</td>\n",
+ " <td>1900</td>\n",
+ " <td>34</td>\n",
+ " <td>Small</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>10</th>\n",
+ " <td>11</td>\n",
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+ " <td>29</td>\n",
+ " <td>Small</td>\n",
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+ " <td>2075</td>\n",
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+ " <td>Small</td>\n",
+ " </tr>\n",
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+ " <th>12</th>\n",
+ " <td>13</td>\n",
+ " <td>2330</td>\n",
+ " <td>26</td>\n",
+ " <td>Small</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>13</th>\n",
+ " <td>14</td>\n",
+ " <td>3320</td>\n",
+ " <td>20</td>\n",
+ " <td>Sporty</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>14</th>\n",
+ " <td>15</td>\n",
+ " <td>2885</td>\n",
+ " <td>27</td>\n",
+ " <td>Sporty</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>15</th>\n",
+ " <td>16</td>\n",
+ " <td>3310</td>\n",
+ " <td>19</td>\n",
+ " <td>Sporty</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>16</th>\n",
+ " <td>17</td>\n",
+ " <td>2695</td>\n",
+ " <td>30</td>\n",
+ " <td>Sporty</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>17</th>\n",
+ " <td>18</td>\n",
+ " <td>2170</td>\n",
+ " <td>33</td>\n",
+ " <td>Sporty</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>18</th>\n",
+ " <td>19</td>\n",
+ " <td>2710</td>\n",
+ " <td>27</td>\n",
+ " <td>Sporty</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>19</th>\n",
+ " <td>20</td>\n",
+ " <td>2775</td>\n",
+ " <td>24</td>\n",
+ " <td>Sporty</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>20</th>\n",
+ " <td>21</td>\n",
+ " <td>2840</td>\n",
+ " <td>26</td>\n",
+ " <td>Sporty</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>21</th>\n",
+ " <td>22</td>\n",
+ " <td>2485</td>\n",
+ " <td>28</td>\n",
+ " <td>Sporty</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>22</th>\n",
+ " <td>23</td>\n",
+ " <td>2670</td>\n",
+ " <td>27</td>\n",
+ " <td>Compact</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>23</th>\n",
+ " <td>24</td>\n",
+ " <td>2640</td>\n",
+ " <td>23</td>\n",
+ " <td>Compact</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>24</th>\n",
+ " <td>25</td>\n",
+ " <td>2655</td>\n",
+ " <td>26</td>\n",
+ " <td>Compact</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>25</th>\n",
+ " <td>26</td>\n",
+ " <td>3065</td>\n",
+ " <td>25</td>\n",
+ " <td>Compact</td>\n",
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+ " <tr>\n",
+ " <th>26</th>\n",
+ " <td>27</td>\n",
+ " <td>2750</td>\n",
+ " <td>24</td>\n",
+ " <td>Compact</td>\n",
+ " </tr>\n",
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+ " <th>27</th>\n",
+ " <td>28</td>\n",
+ " <td>2920</td>\n",
+ " <td>26</td>\n",
+ " <td>Compact</td>\n",
+ " </tr>\n",
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+ " <th>28</th>\n",
+ " <td>29</td>\n",
+ " <td>2780</td>\n",
+ " <td>24</td>\n",
+ " <td>Compact</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>29</th>\n",
+ " <td>30</td>\n",
+ " <td>2745</td>\n",
+ " <td>25</td>\n",
+ " <td>Compact</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>30</th>\n",
+ " <td>31</td>\n",
+ " <td>3110</td>\n",
+ " <td>21</td>\n",
+ " <td>Compact</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>31</th>\n",
+ " <td>32</td>\n",
+ " <td>2920</td>\n",
+ " <td>21</td>\n",
+ " <td>Compact</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>32</th>\n",
+ " <td>33</td>\n",
+ " <td>2645</td>\n",
+ " <td>23</td>\n",
+ " <td>Compact</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>33</th>\n",
+ " <td>34</td>\n",
+ " <td>2575</td>\n",
+ " <td>24</td>\n",
+ " <td>Compact</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>34</th>\n",
+ " <td>35</td>\n",
+ " <td>2935</td>\n",
+ " <td>23</td>\n",
+ " <td>Compact</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>35</th>\n",
+ " <td>36</td>\n",
+ " <td>2920</td>\n",
+ " <td>27</td>\n",
+ " <td>Compact</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>36</th>\n",
+ " <td>37</td>\n",
+ " <td>2985</td>\n",
+ " <td>23</td>\n",
+ " <td>Compact</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>37</th>\n",
+ " <td>38</td>\n",
+ " <td>3265</td>\n",
+ " <td>20</td>\n",
+ " <td>Medium</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>38</th>\n",
+ " <td>39</td>\n",
+ " <td>2880</td>\n",
+ " <td>21</td>\n",
+ " <td>Medium</td>\n",
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+ " <th>39</th>\n",
+ " <td>40</td>\n",
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+ " <td>22</td>\n",
+ " <td>Medium</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>40</th>\n",
+ " <td>41</td>\n",
+ " <td>3450</td>\n",
+ " <td>22</td>\n",
+ " <td>Medium</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>41</th>\n",
+ " <td>42</td>\n",
+ " <td>3145</td>\n",
+ " <td>22</td>\n",
+ " <td>Medium</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>42</th>\n",
+ " <td>43</td>\n",
+ " <td>3190</td>\n",
+ " <td>22</td>\n",
+ " <td>Medium</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>43</th>\n",
+ " <td>44</td>\n",
+ " <td>3610</td>\n",
+ " <td>23</td>\n",
+ " <td>Medium</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>44</th>\n",
+ " <td>45</td>\n",
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+ " <td>21</td>\n",
+ " <td>Medium</td>\n",
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+ " <th>46</th>\n",
+ " <td>47</td>\n",
+ " <td>3200</td>\n",
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+ " <td>Medium</td>\n",
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+ " <td>Medium</td>\n",
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+ " <th>48</th>\n",
+ " <td>49</td>\n",
+ " <td>3220</td>\n",
+ " <td>21</td>\n",
+ " <td>Medium</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>49</th>\n",
+ " <td>50</td>\n",
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+ " <td>23</td>\n",
+ " <td>Medium</td>\n",
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+ " <td>51</td>\n",
+ " <td>3325</td>\n",
+ " <td>23</td>\n",
+ " <td>Large</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>51</th>\n",
+ " <td>52</td>\n",
+ " <td>3855</td>\n",
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+ " <td>3415</td>\n",
+ " <td>20</td>\n",
+ " <td>Van</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>58</th>\n",
+ " <td>59</td>\n",
+ " <td>3185</td>\n",
+ " <td>20</td>\n",
+ " <td>Van</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>59</th>\n",
+ " <td>60</td>\n",
+ " <td>3690</td>\n",
+ " <td>19</td>\n",
+ " <td>Van</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " X weight mpg type\n",
+ "0 1 2560 33 Small\n",
+ "1 2 2345 33 Small\n",
+ "2 3 1845 37 Small\n",
+ "3 4 2260 32 Small\n",
+ "4 5 2440 32 Small\n",
+ "5 6 2285 26 Small\n",
+ "6 7 2275 33 Small\n",
+ "7 8 2350 28 Small\n",
+ "8 9 2295 25 Small\n",
+ "9 10 1900 34 Small\n",
+ "10 11 2390 29 Small\n",
+ "11 12 2075 35 Small\n",
+ "12 13 2330 26 Small\n",
+ "13 14 3320 20 Sporty\n",
+ "14 15 2885 27 Sporty\n",
+ "15 16 3310 19 Sporty\n",
+ "16 17 2695 30 Sporty\n",
+ "17 18 2170 33 Sporty\n",
+ "18 19 2710 27 Sporty\n",
+ "19 20 2775 24 Sporty\n",
+ "20 21 2840 26 Sporty\n",
+ "21 22 2485 28 Sporty\n",
+ "22 23 2670 27 Compact\n",
+ "23 24 2640 23 Compact\n",
+ "24 25 2655 26 Compact\n",
+ "25 26 3065 25 Compact\n",
+ "26 27 2750 24 Compact\n",
+ "27 28 2920 26 Compact\n",
+ "28 29 2780 24 Compact\n",
+ "29 30 2745 25 Compact\n",
+ "30 31 3110 21 Compact\n",
+ "31 32 2920 21 Compact\n",
+ "32 33 2645 23 Compact\n",
+ "33 34 2575 24 Compact\n",
+ "34 35 2935 23 Compact\n",
+ "35 36 2920 27 Compact\n",
+ "36 37 2985 23 Compact\n",
+ "37 38 3265 20 Medium\n",
+ "38 39 2880 21 Medium\n",
+ "39 40 2975 22 Medium\n",
+ "40 41 3450 22 Medium\n",
+ "41 42 3145 22 Medium\n",
+ "42 43 3190 22 Medium\n",
+ "43 44 3610 23 Medium\n",
+ "44 45 2885 23 Medium\n",
+ "45 46 3480 21 Medium\n",
+ "46 47 3200 22 Medium\n",
+ "47 48 2765 21 Medium\n",
+ "48 49 3220 21 Medium\n",
+ "49 50 3480 23 Medium\n",
+ "50 51 3325 23 Large\n",
+ "51 52 3855 18 Large\n",
+ "52 53 3850 20 Large\n",
+ "53 54 3195 18 Van\n",
+ "54 55 3735 18 Van\n",
+ "55 56 3665 18 Van\n",
+ "56 57 3735 19 Van\n",
+ "57 58 3415 20 Van\n",
+ "58 59 3185 20 Van\n",
+ "59 60 3690 19 Van"
+ ]
+ },
+ "execution_count": 44,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
"# First import Pandas\n",
"import pandas as pd\n",
"\n",
"# load the database using pandas.read_csv. The file location is different for everyone. If you made a new folder in this folder named \"data\", the path would be ./data/d.fuel.dat\n",
"# Example: data = pd.read_csv(\"/data/d.fuel.dat\")\n",
- "data = None\n",
+ "data = pd.read_csv(\"./data/d.fuel.dat\")\n",
"\n",
"data"
]
@@ -747,20 +1268,184 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 47,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<style scoped>\n",
+ " .dataframe tbody tr th:only-of-type {\n",
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+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>X</th>\n",
+ " <th>weight</th>\n",
+ " <th>mpg</th>\n",
+ " <th>type</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>1</td>\n",
+ " <td>2560</td>\n",
+ " <td>33</td>\n",
+ " <td>Small</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
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+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>3</td>\n",
+ " <td>1845</td>\n",
+ " <td>37</td>\n",
+ " <td>Small</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>4</td>\n",
+ " <td>2260</td>\n",
+ " <td>32</td>\n",
+ " <td>Small</td>\n",
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+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>5</td>\n",
+ " <td>2440</td>\n",
+ " <td>32</td>\n",
+ " <td>Small</td>\n",
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+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " X weight mpg type\n",
+ "0 1 2560 33 Small\n",
+ "1 2 2345 33 Small\n",
+ "2 3 1845 37 Small\n",
+ "3 4 2260 32 Small\n",
+ "4 5 2440 32 Small"
+ ]
+ },
+ "execution_count": 47,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
- "# Print the first 5 rows using data.loc\n"
+ "# Print the first 5 rows using data.loc\n",
+ "data.loc[:4,]"
]
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": 46,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
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+ " .dataframe tbody tr th:only-of-type {\n",
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+ " .dataframe tbody tr th {\n",
+ " vertical-align: top;\n",
+ " }\n",
+ "\n",
+ " .dataframe thead th {\n",
+ " text-align: right;\n",
+ " }\n",
+ "</style>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>X</th>\n",
+ " <th>weight</th>\n",
+ " <th>mpg</th>\n",
+ " <th>type</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>1</td>\n",
+ " <td>2560</td>\n",
+ " <td>33</td>\n",
+ " <td>Small</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>2</td>\n",
+ " <td>2345</td>\n",
+ " <td>33</td>\n",
+ " <td>Small</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>3</td>\n",
+ " <td>1845</td>\n",
+ " <td>37</td>\n",
+ " <td>Small</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>4</td>\n",
+ " <td>2260</td>\n",
+ " <td>32</td>\n",
+ " <td>Small</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>5</td>\n",
+ " <td>2440</td>\n",
+ " <td>32</td>\n",
+ " <td>Small</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " X weight mpg type\n",
+ "0 1 2560 33 Small\n",
+ "1 2 2345 33 Small\n",
+ "2 3 1845 37 Small\n",
+ "3 4 2260 32 Small\n",
+ "4 5 2440 32 Small"
+ ]
+ },
+ "execution_count": 46,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
- "# print the first 5 rows using data.head()\n"
+ "# print the first 5 rows using data.head()\n",
+ "data.head()"
]
},
{
@@ -775,7 +1460,7 @@
},
{
"cell_type": "code",
- "execution_count": 20,
+ "execution_count": 76,
"metadata": {},
"outputs": [
{
@@ -783,17 +1468,17 @@
"output_type": "stream",
"text": [
"Average miles per galon is: \n",
- "0 \n",
+ "24.58 \n",
"Average miles per galon for all Medium type cars is: \n",
- "0\n"
+ "21.77\n"
]
}
],
"source": [
- "avg_mpg = 0\n",
- "avg_medium = 0\n",
+ "avg_mpg = data.loc[:, \"mpg\"].mean()\n",
+ "avg_medium = data[data[\"type\"].isin([\"Medium\"])].loc[:, \"mpg\"].mean()\n",
"\n",
- "print(\"Average miles per galon is: \\n{}\".format(round(avg_mpg, 2)), \"\\nAverage miles per galon for all Medium type cars is: \\n{}\".format(round(avg_medium,2)))"
+ "print(\"Average miles per galon is: \\n{}\".format(round(avg_mpg, 2)), \"\\nAverage miles per galon for all Medium type cars is: \\n{}\".format(round(avg_medium, 2)))"
]
},
{
@@ -807,30 +1492,36 @@
},
{
"cell_type": "code",
- "execution_count": 27,
+ "execution_count": 78,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Empty DataFrame\n",
- "Columns: []\n",
- "Index: []\n",
- "Empty DataFrame\n",
- "Columns: []\n",
- "Index: []\n",
+ "0 14.018470\n",
+ "1 14.018470\n",
+ "2 15.717678\n",
+ "3 13.593668\n",
+ "4 13.593668\n",
+ "Name: mpg, dtype: float64\n",
+ "0 1162.24\n",
+ "1 1064.63\n",
+ "2 837.63\n",
+ "3 1026.04\n",
+ "4 1107.76\n",
+ "Name: weight, dtype: float64\n",
"\n",
"Average Kilometer per liter is: \n",
- "Series([], dtype: float64) \n",
+ "10.44 \n",
"Average weight in kilogram is: \n",
- "Series([], dtype: float64)\n"
+ "1316.98\n"
]
}
],
"source": [
- "t_kml = pd.DataFrame()\n",
- "t_kg = pd.DataFrame()\n",
+ "t_kml = data.loc[:, \"mpg\"]*1.61/3.79\n",
+ "t_kg = data.loc[:, \"weight\"]*0.454\n",
"\n",
"print(t_kml.head())\n",
"print(t_kg.head())\n",