Power-BI / Food Forecasting / fulfilment_center_info.csv
fulfilment_center_info.csv
Raw
center_id,city_code,region_code,center_type,op_area
11,679,56,TYPE_A,3.7
13,590,56,TYPE_B,6.7
124,590,56,TYPE_C,4
66,648,34,TYPE_A,4.1
94,632,34,TYPE_C,3.6
64,553,77,TYPE_A,4.4
129,593,77,TYPE_A,3.9
139,693,34,TYPE_C,2.8
88,526,34,TYPE_A,4.1
143,562,77,TYPE_B,3.8
101,699,85,TYPE_C,2.8
86,699,85,TYPE_C,4
32,526,34,TYPE_A,3.8
149,478,77,TYPE_A,2.4
152,576,34,TYPE_B,4
92,526,34,TYPE_C,2.9
27,713,85,TYPE_A,4.5
14,654,56,TYPE_C,2.7
26,515,77,TYPE_C,3
104,647,56,TYPE_A,4.5
77,676,34,TYPE_A,3.8
23,698,23,TYPE_A,3.4
97,628,77,TYPE_A,4.6
146,526,34,TYPE_B,5
113,680,77,TYPE_C,4
145,620,77,TYPE_A,3.9
80,604,56,TYPE_C,5.1
55,647,56,TYPE_C,2
186,649,34,TYPE_A,3.4
99,596,71,TYPE_A,4.5
91,590,56,TYPE_C,0.9
20,522,56,TYPE_A,4
106,675,34,TYPE_A,4
81,526,34,TYPE_A,4
73,576,34,TYPE_A,4
29,526,34,TYPE_C,4
43,590,56,TYPE_A,5.1
102,593,77,TYPE_A,2.8
61,473,77,TYPE_A,4.5
50,556,77,TYPE_A,4.8
83,659,77,TYPE_A,5.3
57,541,77,TYPE_C,2.8
126,577,56,TYPE_A,2.7
177,683,56,TYPE_A,3.4
67,638,56,TYPE_B,7
174,700,56,TYPE_A,7
59,456,56,TYPE_A,4.2
58,695,77,TYPE_C,3.8
65,602,34,TYPE_A,4.8
39,526,34,TYPE_C,3.8
132,522,56,TYPE_A,3.9
89,703,56,TYPE_A,4.8
162,526,34,TYPE_C,2
75,651,77,TYPE_B,4.7
72,638,56,TYPE_C,3.9
41,590,56,TYPE_C,1.9
10,590,56,TYPE_B,6.3
110,485,77,TYPE_A,3.8
52,685,56,TYPE_B,5.6
93,461,34,TYPE_A,3.9
74,702,35,TYPE_A,2.8
34,615,34,TYPE_B,4.2
137,590,56,TYPE_A,4.4
153,590,56,TYPE_A,3.9
24,614,85,TYPE_B,3.6
109,599,56,TYPE_A,3.6
108,579,56,TYPE_B,4.4
36,517,56,TYPE_B,4.4
157,609,93,TYPE_A,4.1
17,517,56,TYPE_A,3.2
161,658,34,TYPE_B,3.9
42,561,77,TYPE_B,3.9
53,590,56,TYPE_A,3.8
30,604,56,TYPE_A,3.5
76,614,85,TYPE_A,3
68,676,34,TYPE_B,4.1
51,638,56,TYPE_A,7