Table:
No
Name
Code
Formed
Headquarters
Administrative
Division
Area (km2)
Population
(2001 census)
% of State
Population
Density
(per km2)
Urban (%)
Literacy (%)
Sex Ratio
Tehsils
Source

1
Ahmednagar
AH
1 May 1960
Ahmednagar
Nashik
17,413
4,088,077
4.22%
234.77
19.67
75.82
941
14
District website

2
Akola
AK
1 May 1960
Akola
Amravati
5,417
1,818,617
1.68%
300.78
38.49
81.41
938
7
District website

3
Amravati
AM
1 May 1960
Amravati
Amravati
12,626
2,606,063
2.69%
206.40
34.50
82.5
938
14
District website

4
Aurangabad
AU
1 May 1960
Aurangabad
Aurangabad
10,100
2,897,013
2.99%
286.83
37.53
61.15
924
9
District website

5
Beed
BI
1 May 1960
Beed
Aurangabad
10,439
2,161,250
2.23%
207.04
17.91
68
936
11
District website

6
Bhandara
BH
1 May 1960
Bhandara
Nagpur
3,717
1,135,835
1.17%
305.58
15.44
68.28
982
7
District website

7
Buldhana
BU
1 May 1960
Buldhana
Amravati
9,680
2,232,480
2.3%
230.63
21.2
75.8
946
13
District website

8
Chandrapur
CH
1 May 1960
Chandrapur
Nagpur
10,695
2,071,101
2.14%
193.65
32.11
73.03
948
15
District website

9
Dhule
DH
1 May 1960
Dhule
Nashik
8,063
1,707,947
1.76%
211.83
26.11
71.6
944
4
District website

10
Gadchiroli
GA
26 August 1982
Gadchiroli
Nagpur
14,412
970,294
1%
67.33
6.93
60.1
976
12
District website

11
Gondia
GO
1 May 1999
Gondia
Nagpur
4,843
1,200,151
1.24%
247.81
11.95
67.67
1005
8
District website

12
Hingoli
HI
1 May 1999
Hingoli
Aurangabad
4,526
987,160
1.02%
218.11
15.2
66.86
953
5
District website

13
Jalgaon
JG
1 May 1960
Jalgaon
Nashik
11,765
3,679,936
3.8%
312.79
71.4
76.06
932
15
District website

14
Jalna
JN
1 May 1981
Jalna
Aurangabad
7,612
1,612,357
1.66%
211.82
19.09
64.52
952
8
District website

15
Kolhapur
KO
1 May 1960
Kolhapur
Pune
7,685
3,515,413
3.63%
457.44
29.65
77.23
949
10
District website

16
Latur
LA
15 August 1982
Latur
Aurangabad
7,372
2,080,285
2.15%
282.19
23.57
71.54
935
10
District website

17
Mumbai City
MC
1 May 1960
Mumbai
Konkan
67.7
3,326,837
3.43%
49,140.9
100
86.4
777
0
District website

18
Mumbai Suburban
MU
1 October 1990
Bandra (East)
Konkan
369
8,587,000
8.86%
23,271
100
86.9
822
3
District website

19
Nagpur
NG
1 May 1960
Nagpur
Nagpur
9,897
4,051,444
4.18%
409.36
64.33
84.18
933
13
District website

20
Nanded
ND
1 May 1960
Nanded
Aurangabad
10,422
2,876,259
2.97%
275.98
28.29
68.52
942
16
District website

21
Nandurbar
NB
1 July 1998
Nandurbar
Nashik
5,035
1,309,135
1.35%
260
15.5
46.63
975
6
District website

22
Nashik
NS
1 May 1960
Nashik
Nashik
15,530
4,993,796
5.15%
321.56
38.8
74.4
927
15
District website

23
Osmanabad
OS
1 May 1960
Osmanabad
Aurangabad
7,512
1,486,586
1.53%
197.89
15.7
54.27
932
8
District website

24
Parbhani
PA
1 May 1960
Parbhani
Aurangabad
6,251
1,527,715
1.58%
244.4
31.8
55.15
958
9
District website

25
Pune
PU
1 May 1960
Pune
Pune
15,642
7,224,224
7.46%
461.85
58.1
80.78
919
14
District website

26
Raigad
RG
1 May 1960
Alibag
Konkan
7,148
2,207,929
2.28%
308.89
24.2
77
976
15
District website

27
Ratnagiri
RT
1 May 1960
Ratnagiri
Konkan
8,208
1,696,777
1.75%
206.72
11.3
65.13
1,136
9
District website

28
Sangli
SN
1 May 1960
Sangli
Pune
8,578
2,583,524
2.67%
301.18
24.5
62.41
957
10
District website

29
Satara
ST
1 May 1960
Satara
Pune
10,484
2,796,906
2.89%
266.77
14.2
78.52
995
11
District website

30
Sindhudurg
SI
1 May 1981
Oros
Konkan
5,207
868,825
0.9%
166.86
9.5
80.3
1,079
8
District website

31
Solapur
SO
1 May 1960
Daund
Pune
14,845
3,849,543
3.97%
259.32
31.8
71.2
935
11
District website

32
Thane
TH
1 May 1960
Thane
Konkan
9,558
8,131,849
8.39%
850.71
72.58
80.67
858
15
District website

33
Wardha
WR
1 May 1960
Wardha
Nagpur
6,310
1,230,640
1.27%
195.03
25.17
80.5
936
8
District website

34
Washim
WS
1 July 1998
Washim
Amravati
5,150
1,020,216
1.05%
275.98
17.49
74.02
939
6
District website

35
Yavatmal
YA
1 May 1960
Yavatmal
Amravati
13,582
2,077,144
2.14%
152.93
18.6
57.96
951
16
District website

Maharashtra
-
-
-
-
-
307,713
96,878,627
-
314.42
42.43
77.27
922
-
-

Provide the content of the cell located in row 16 and column 5 of this table. Return the cell value as JSON in the format {"row_id":"m", "column_id":"n", "cell_value":"<Corresponding Cell Value>"}.

The target cell value in row 16 and column 5 is {"row_id":"16", "column_id":"5", "cell_value":"Kolhapur"}.