Wine¶

Introduction:¶

This exercise is a adaptation from the UCI Wine dataset. The only pupose is to practice deleting data with pandas.

Step 1. Import the necessary libraries¶

In [2]:

Step 2. Import the dataset from this address.¶

Step 3. Assign it to a variable called wine¶

In [3]:

Out[3]:

	1	14.23	1.71	2.43	15.6	127	2.8	3.06	.28	2.29	5.64	1.04	3.92	1065
0	1	13.20	1.78	2.14	11.2	100	2.65	2.76	0.26	1.28	4.38	1.05	3.40	1050
1	1	13.16	2.36	2.67	18.6	101	2.80	3.24	0.30	2.81	5.68	1.03	3.17	1185
2	1	14.37	1.95	2.50	16.8	113	3.85	3.49	0.24	2.18	7.80	0.86	3.45	1480
3	1	13.24	2.59	2.87	21.0	118	2.80	2.69	0.39	1.82	4.32	1.04	2.93	735
4	1	14.20	1.76	2.45	15.2	112	3.27	3.39	0.34	1.97	6.75	1.05	2.85	1450

Step 4. Delete the first, fourth, seventh, nineth, eleventh, thirteenth and fourteenth columns¶

In [4]:

Out[4]:

	14.23	1.71	15.6	127	3.06	2.29	5.64
0	13.20	1.78	11.2	100	2.76	1.28	4.38
1	13.16	2.36	18.6	101	3.24	2.81	5.68
2	14.37	1.95	16.8	113	3.49	2.18	7.80
3	13.24	2.59	21.0	118	2.69	1.82	4.32
4	14.20	1.76	15.2	112	3.39	1.97	6.75

Step 5. Assign the columns as below:¶

The attributes are (donated by Riccardo Leardi, riclea '@' anchem.unige.it):

alcohol
malic_acid
alcalinity_of_ash
magnesium
flavanoids
proanthocyanins
hue

In [5]:

Out[5]:

	alcohol	malic_acid	alcalinity_of_ash	magnesium	flavanoids	proanthocyanins	hue
0	13.20	1.78	11.2	100	2.76	1.28	4.38
1	13.16	2.36	18.6	101	3.24	2.81	5.68
2	14.37	1.95	16.8	113	3.49	2.18	7.80
3	13.24	2.59	21.0	118	2.69	1.82	4.32
4	14.20	1.76	15.2	112	3.39	1.97	6.75

Step 6. Set the values of the first 3 rows from alcohol as NaN¶

In [6]:

Out[6]:

	alcohol	malic_acid	alcalinity_of_ash	magnesium	flavanoids	proanthocyanins	hue
0	NaN	1.78	11.2	100	2.76	1.28	4.38
1	NaN	2.36	18.6	101	3.24	2.81	5.68
2	NaN	1.95	16.8	113	3.49	2.18	7.80
3	13.24	2.59	21.0	118	2.69	1.82	4.32
4	14.20	1.76	15.2	112	3.39	1.97	6.75

Step 7. Now set the value of the rows 3 and 4 of magnesium as NaN¶

In [7]:

Out[7]:

	alcohol	malic_acid	alcalinity_of_ash	magnesium	flavanoids	proanthocyanins	hue
0	NaN	1.78	11.2	100.0	2.76	1.28	4.38
1	NaN	2.36	18.6	101.0	3.24	2.81	5.68
2	NaN	1.95	16.8	NaN	3.49	2.18	7.80
3	13.24	2.59	21.0	NaN	2.69	1.82	4.32
4	14.20	1.76	15.2	112.0	3.39	1.97	6.75

Step 8. Fill the value of NaN with the number 10 in alcohol and 100 in magnesium¶

In [8]:

Out[8]:

	alcohol	malic_acid	alcalinity_of_ash	magnesium	flavanoids	proanthocyanins	hue
0	10.00	1.78	11.2	100.0	2.76	1.28	4.38
1	10.00	2.36	18.6	101.0	3.24	2.81	5.68
2	10.00	1.95	16.8	100.0	3.49	2.18	7.80
3	13.24	2.59	21.0	100.0	2.69	1.82	4.32
4	14.20	1.76	15.2	112.0	3.39	1.97	6.75

Step 9. Count the number of missing values¶

In [9]:

Out[9]:

alcohol              0
malic_acid           0
alcalinity_of_ash    0
magnesium            0
flavanoids           0
proanthocyanins      0
hue                  0
dtype: int64

Step 10. Create an array of 10 random numbers up until 10¶

In [10]:

Out[10]:

array([2, 3, 0, 5, 0, 9, 4, 0, 7, 2])

Step 11. Use random numbers you generated as an index and assign NaN value to each of cell.¶

In [11]:

Out[11]:

	alcohol	malic_acid	alcalinity_of_ash	magnesium	flavanoids	proanthocyanins	hue
0	NaN	1.78	11.2	100.0	2.76	1.28	4.38
1	10.00	2.36	18.6	101.0	3.24	2.81	5.68
2	NaN	1.95	16.8	100.0	3.49	2.18	7.80
3	NaN	2.59	21.0	100.0	2.69	1.82	4.32
4	NaN	1.76	15.2	112.0	3.39	1.97	6.75
5	NaN	1.87	14.6	96.0	2.52	1.98	5.25
6	14.06	2.15	17.6	121.0	2.51	1.25	5.05
7	NaN	1.64	14.0	97.0	2.98	1.98	5.20
8	13.86	1.35	16.0	98.0	3.15	1.85	7.22
9	NaN	2.16	18.0	105.0	3.32	2.38	5.75

Step 12. How many missing values do we have?¶

In [12]:

Out[12]:

alcohol              7
malic_acid           0
alcalinity_of_ash    0
magnesium            0
flavanoids           0
proanthocyanins      0
hue                  0
dtype: int64

Step 13. Delete the rows that contain missing values¶

In [13]:

Out[13]:

	alcohol	malic_acid	alcalinity_of_ash	magnesium	flavanoids	proanthocyanins	hue
1	10.00	2.36	18.6	101.0	3.24	2.81	5.68
6	14.06	2.15	17.6	121.0	2.51	1.25	5.05
8	13.86	1.35	16.0	98.0	3.15	1.85	7.22
10	14.12	1.48	16.8	95.0	2.43	1.57	5.00
11	13.75	1.73	16.0	89.0	2.76	1.81	5.60

Step 14. Print only the non-null values in alcohol¶

In [14]:

Out[14]:

1      True
6      True
8      True
10     True
11     True
12     True
13     True
14     True
15     True
16     True
17     True
18     True
19     True
20     True
21     True
22     True
23     True
24     True
25     True
26     True
27     True
28     True
29     True
30     True
31     True
32     True
33     True
34     True
35     True
36     True
       ... 
147    True
148    True
149    True
150    True
151    True
152    True
153    True
154    True
155    True
156    True
157    True
158    True
159    True
160    True
161    True
162    True
163    True
164    True
165    True
166    True
167    True
168    True
169    True
170    True
171    True
172    True
173    True
174    True
175    True
176    True
Name: alcohol, dtype: bool

In [15]:

Out[15]:

1      10.00
6      14.06
8      13.86
10     14.12
11     13.75
12     14.75
13     14.38
14     13.63
15     14.30
16     13.83
17     14.19
18     13.64
19     14.06
20     12.93
21     13.71
22     12.85
23     13.50
24     13.05
25     13.39
26     13.30
27     13.87
28     14.02
29     13.73
30     13.58
31     13.68
32     13.76
33     13.51
34     13.48
35     13.28
36     13.05
       ...  
147    13.32
148    13.08
149    13.50
150    12.79
151    13.11
152    13.23
153    12.58
154    13.17
155    13.84
156    12.45
157    14.34
158    13.48
159    12.36
160    13.69
161    12.85
162    12.96
163    13.78
164    13.73
165    13.45
166    12.82
167    13.58
168    13.40
169    12.20
170    12.77
171    14.16
172    13.71
173    13.40
174    13.27
175    13.17
176    14.13
Name: alcohol, dtype: float64

Step 15. Reset the index, so it starts with 0 again¶

In [16]:

Out[16]:

	alcohol	malic_acid	alcalinity_of_ash	magnesium	flavanoids	proanthocyanins	hue
0	10.00	2.36	18.6	101.0	3.24	2.81	5.68
1	14.06	2.15	17.6	121.0	2.51	1.25	5.05
2	13.86	1.35	16.0	98.0	3.15	1.85	7.22
3	14.12	1.48	16.8	95.0	2.43	1.57	5.00
4	13.75	1.73	16.0	89.0	2.76	1.81	5.60

BONUS: Create your own question and answer it.¶

In [ ]: