- 1 2 3 4 5 6 7 8 9 10 11
- ----------- ----------- ----------- ----------- --------------- ---------------- ------------------ ---------------- --------- ---------- -----------
0 Chennai Guwahati Pune New Delhi Visakhapatnam Bhopal Ahmedabad Indore Ludhiana Coimbatore Belagaavi
1 Lucknow Warangal Dharamasala Agartala Raipur New Town Kolkata Ranchi Panaji Imphal Chandigarh Port Blair
2 Kanpur Ajmer Salem Aurangabad Rourkela Kota Hubli-Dharwad Kalyan Thanjavur Tumakuru Vellore
3 Tirunelveli Naya Raipur Prayagraj Bangalore Thoothukudi Puducherry Shimla Pimpri Chinchwad Karnal Satna Gandhinagar
4 Shillong Kavaratti Silvassa Itanagar Moradabad Bihar Sharif Bhubaneswar Saharanpur Erode Bareilly Diu
5 Bhagalpur Jabalpur Jaipur Udaipur Faridabad Kochi Kohima Solapur Surat Davangere Kakinada
6 Gwalior Vadodara Nagpur Thane Namchi Nashik Shimoga Jalandhar Tirupati Dehradun Varanasi
7 Madurai Rajkot Aligarh Muzaffarpur Dahod Aizawl Thiruvananthapuram Amravati Sagar Jhansi Gangtok
8 Ujjain Bilaspur Mangalore Agra Tiruchirappalli Jammu Pasighat Karimnagar Amritsar Patna Tiruppur
9 Srinagar
- ----------- ----------- ----------- ----------- --------------- ---------------- ------------------ ---------------- --------- ---------- -----------
import json
import numpy as np
import pandas as pd
from tabulate import tabulate
def allocate():
with open('city.json', 'r') as f:
data = json.load(f)
cities_list = []
for k, v in data.items():
cities_list.append(np.random.permutation(v).tolist())
#print(cities_list)
group_list = []
while len(group_list) < 100:
for i, c in enumerate(cities_list):
if len(c) > 10:
group_list = group_list + c[:11]
cities_list[i] = c[11:]
else:
group_list = group_list + c[:]
cities_list[i] = []
#print(group_list)
final = []
for i in range(0, 99, 11):
#print(np.random.permutation(group_list[i:i+11]).tolist())
print(i)
final.append(np.random.permutation(group_list[i:i+11]).tolist())
final.append([""]*11)
pd_data = pd.DataFrame(final, columns=range(1, 12))
pd_data.iloc[9, np.random.randint(0,2)] = group_list[99]
return pd_data
if '__main__' == __name__:
print(tabulate(allocate(), tablefmt="text")){
"round1": [
"Bhubaneswar",
"Pune",
"Jaipur",
"Surat",
"Kochi",
"Ahmedabad",
"Jabalpur",
"Visakhapatnam",
"Solapur",
"Davangere",
"Indore",
"New Delhi",
"Coimbatore",
"Kakinada",
"Belagaavi",
"Udaipur",
"Guwahati",
"Chennai",
"Ludhiana",
"Bhopal"
],
"round2": [
"Lucknow",
"Bhagalpur",
"Faridabad",
"Chandigarh",
"Raipur",
"Ranchi",
"Dharamasala",
"Warangal",
"Panaji",
"Agartala",
"Imphal",
"Port Blair",
"New Town Kolkata"
],
"round3": [
"Amritsar",
"Kalyan",
"Ujjain",
"Tirupati",
"Nagpur",
"Mangalore",
"Vellore",
"Thane",
"Gwalior",
"Agra",
"Nashik",
"Rourkela",
"Kanpur",
"Madurai",
"Tumakuru",
"Kota",
"Thanjavur",
"Namchi",
"Jalandhar",
"Shimoga",
"Salem",
"Ajmer",
"Varanasi",
"Kohima",
"Hubli-Dharwad",
"Aurangabad",
"Vadodara"
],
"round4": [
"Thiruvananthapuram",
"Naya Raipur",
"Rajkot",
"Amravati",
"Patna",
"Karimnagar",
"Muzaffarpur",
"Puducherry",
"Gandhinagar",
"Srinagar",
"Sagar",
"Karnal",
"Satna",
"Bangalore",
"Shimla",
"Dehradun",
"Jhansi",
"Pimpri Chinchwad",
"Bilaspur",
"Pasighat",
"Jammu",
"Dahod",
"Thoothukudi",
"Tiruchirappalli",
"Tirunelveli",
"Tiruppur",
"Aizawl",
"Prayagraj",
"Aligarh",
"Gangtok"
],
"round5": [
"Erode",
"Saharanpur",
"Moradabad",
"Bareilly",
"Itanagar",
"Silvassa",
"Diu",
"Kavaratti",
"Bihar Sharif",
"Shillong"
]
}