Overview

Dataset statistics

Number of variables7
Number of observations94
Missing cells12
Missing cells (%)1.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.4 KiB
Average record size in memory58.4 B

Variable types

Numeric1
Text3
Categorical3

Dataset

Description국립부여박물관 유물정보DB입니다. '유물명, 유물번호, 국적/시대, 재질, 출토지, 전시실' 정보를 포함하고 있습니다.
Author문화체육관광부 국립중앙박물관
URLhttps://www.data.go.kr/data/3078546/fileData.do

Alerts

번호 is highly overall correlated with 전시실High correlation
국적/시대 is highly overall correlated with 전시실High correlation
전시실 is highly overall correlated with 번호 and 1 other fieldsHigh correlation
유물번호 has 5 (5.3%) missing valuesMissing
출토지 has 7 (7.4%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:33:40.927035
Analysis finished2023-12-12 13:33:41.917965
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.5
Minimum1
Maximum94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2023-12-12T22:33:42.009119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.65
Q124.25
median47.5
Q370.75
95-th percentile89.35
Maximum94
Range93
Interquartile range (IQR)46.5

Descriptive statistics

Standard deviation27.279418
Coefficient of variation (CV)0.57430354
Kurtosis-1.2
Mean47.5
Median Absolute Deviation (MAD)23.5
Skewness0
Sum4465
Variance744.16667
MonotonicityStrictly increasing
2023-12-12T22:33:42.173629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
61 1
 
1.1%
70 1
 
1.1%
69 1
 
1.1%
68 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
Other values (84) 84
89.4%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
94 1
1.1%
93 1
1.1%
92 1
1.1%
91 1
1.1%
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%

유물명
Text

Distinct92
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size884.0 B
2023-12-12T22:33:42.499617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length16
Mean length7.287234
Min length2

Characters and Unicode

Total characters685
Distinct characters198
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)95.7%

Sample

1st row대쪽모양 동기
2nd row유리 대롱옥
3rd row송국리식토기
4th row서산 휴암리유적 출토 민무늬 토기·골아가리 토기
5th row대롱옥
ValueCountFrequency (%)
벽돌 10
 
5.6%
무늬 6
 
3.4%
출토 3
 
1.7%
토기 3
 
1.7%
도깨비 3
 
1.7%
굽단지 2
 
1.1%
분청사기 2
 
1.1%
새겨진 2
 
1.1%
동기 2
 
1.1%
모양 2
 
1.1%
Other values (136) 144
80.4%
2023-12-12T22:33:43.027148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
85
 
12.4%
기 25
 
3.6%
토 20
 
2.9%
리 18
 
2.6%
동 15
 
2.2%
사 14
 
2.0%
돌 13
 
1.9%
늬 11
 
1.6%
지 11
 
1.6%
금 11
 
1.6%
Other values (188) 462
67.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 587
85.7%
Space Separator 85
 
12.4%
Final Punctuation 4
 
0.6%
Other Punctuation 3
 
0.4%
Initial Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 25
 
4.3%
토 20
 
3.4%
리 18
 
3.1%
동 15
 
2.6%
사 14
 
2.4%
돌 13
 
2.2%
늬 11
 
1.9%
지 11
 
1.9%
금 11
 
1.9%
양 11
 
1.9%
Other values (179) 438
74.6%
Other Punctuation
ValueCountFrequency (%)
· 2
66.7%
, 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 1
50.0%
」 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 1
50.0%
「 1
50.0%
Space Separator
ValueCountFrequency (%)
85
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 4
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 587
85.7%
Common 98
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 25
 
4.3%
토 20
 
3.4%
리 18
 
3.1%
동 15
 
2.6%
사 14
 
2.4%
돌 13
 
2.2%
늬 11
 
1.9%
지 11
 
1.9%
금 11
 
1.9%
양 11
 
1.9%
Other values (179) 438
74.6%
Common
ValueCountFrequency (%)
85
86.7%
’ 4
 
4.1%
‘ 2
 
2.0%
· 2
 
2.0%
) 1
 
1.0%
, 1
 
1.0%
( 1
 
1.0%
」 1
 
1.0%
「 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 587
85.7%
ASCII 88
 
12.8%
Punctuation 6
 
0.9%
None 4
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
85
96.6%
) 1
 
1.1%
, 1
 
1.1%
( 1
 
1.1%
Hangul
ValueCountFrequency (%)
기 25
 
4.3%
토 20
 
3.4%
리 18
 
3.1%
동 15
 
2.6%
사 14
 
2.4%
돌 13
 
2.2%
늬 11
 
1.9%
지 11
 
1.9%
금 11
 
1.9%
양 11
 
1.9%
Other values (179) 438
74.6%
Punctuation
ValueCountFrequency (%)
’ 4
66.7%
‘ 2
33.3%
None
ValueCountFrequency (%)
· 2
50.0%
」 1
25.0%
「 1
25.0%

유물번호
Text

MISSING 

Distinct89
Distinct (%)100.0%
Missing5
Missing (%)5.3%
Memory size884.0 B
2023-12-12T22:33:43.344743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length13
Mean length13.775281
Min length3

Characters and Unicode

Total characters1226
Distinct characters36
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)100.0%

Sample

1st row부여(扶餘)-002299
2nd row부여(扶餘)-003390, 003385
3rd row부여(扶餘)-002139
4th row신수(新收)-010887
5th row부여(扶餘)-002138
ValueCountFrequency (%)
부여(扶餘)-017232 1
 
1.0%
신수(新收)-010887 1
 
1.0%
본관(本館)-013968-002 1
 
1.0%
부여(扶餘)-000071 1
 
1.0%
부여(扶餘)-000014 1
 
1.0%
000355 1
 
1.0%
001059 1
 
1.0%
부여(扶餘)-006808 1
 
1.0%
부여(扶餘)-003274 1
 
1.0%
부여(扶餘)-000285 1
 
1.0%
Other values (86) 86
89.6%
2023-12-12T22:33:43.914427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 254
20.7%
- 98
 
8.0%
( 83
 
6.8%
) 83
 
6.8%
부 77
 
6.3%
扶 75
 
6.1%
餘 75
 
6.1%
여 75
 
6.1%
3 64
 
5.2%
2 55
 
4.5%
Other values (26) 287
23.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 595
48.5%
Other Letter 348
28.4%
Dash Punctuation 98
 
8.0%
Open Punctuation 83
 
6.8%
Close Punctuation 83
 
6.8%
Other Punctuation 9
 
0.7%
Space Separator 7
 
0.6%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 77
22.1%
扶 75
21.6%
餘 75
21.6%
여 75
21.6%
신 4
 
1.1%
수 4
 
1.1%
本 4
 
1.1%
관 4
 
1.1%
본 4
 
1.1%
館 4
 
1.1%
Other values (10) 22
 
6.3%
Decimal Number
ValueCountFrequency (%)
0 254
42.7%
3 64
 
10.8%
2 55
 
9.2%
1 46
 
7.7%
4 36
 
6.1%
5 33
 
5.5%
7 30
 
5.0%
6 29
 
4.9%
8 26
 
4.4%
9 22
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 98
100.0%
Open Punctuation
ValueCountFrequency (%)
( 83
100.0%
Close Punctuation
ValueCountFrequency (%)
) 83
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 875
71.4%
Hangul 182
 
14.8%
Han 166
 
13.5%
Latin 3
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 254
29.0%
- 98
 
11.2%
( 83
 
9.5%
) 83
 
9.5%
3 64
 
7.3%
2 55
 
6.3%
1 46
 
5.3%
4 36
 
4.1%
5 33
 
3.8%
7 30
 
3.4%
Other values (5) 93
 
10.6%
Hangul
ValueCountFrequency (%)
부 77
42.3%
여 75
41.2%
신 4
 
2.2%
수 4
 
2.2%
관 4
 
2.2%
본 4
 
2.2%
번 3
 
1.6%
대 2
 
1.1%
박 2
 
1.1%
위 2
 
1.1%
Other values (4) 5
 
2.7%
Han
ValueCountFrequency (%)
扶 75
45.2%
餘 75
45.2%
本 4
 
2.4%
館 4
 
2.4%
收 4
 
2.4%
新 4
 
2.4%
Latin
ValueCountFrequency (%)
M 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 878
71.6%
Hangul 182
 
14.8%
CJK 166
 
13.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 254
28.9%
- 98
 
11.2%
( 83
 
9.5%
) 83
 
9.5%
3 64
 
7.3%
2 55
 
6.3%
1 46
 
5.2%
4 36
 
4.1%
5 33
 
3.8%
7 30
 
3.4%
Other values (6) 96
 
10.9%
Hangul
ValueCountFrequency (%)
부 77
42.3%
여 75
41.2%
신 4
 
2.2%
수 4
 
2.2%
관 4
 
2.2%
본 4
 
2.2%
번 3
 
1.6%
대 2
 
1.1%
박 2
 
1.1%
위 2
 
1.1%
Other values (4) 5
 
2.7%
CJK
ValueCountFrequency (%)
扶 75
45.2%
餘 75
45.2%
本 4
 
2.4%
館 4
 
2.4%
收 4
 
2.4%
新 4
 
2.4%

국적/시대
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)13.8%
Missing0
Missing (%)0.0%
Memory size884.0 B
한국(韓國)-백제(百濟)
59 
한국(韓國)-청동기(靑銅器)
10 
한국(韓國)-초기철기(初期鐵器)
7 
한국(韓國)-고려(高麗)
 
5
한국(韓國)-원삼국(原三國)
 
4
Other values (8)
9 

Length

Max length23
Median length13
Mean length13.648936
Min length2

Unique

Unique7 ?
Unique (%)7.4%

Sample

1st row한국(韓國)-초기철기(初期鐵器)
2nd row한국(韓國)-초기철기(初期鐵器)
3rd row한국(韓國)-청동기(靑銅器)
4th row한국(韓國)-청동기(靑銅器)
5th row한국(韓國)-청동기(靑銅器)

Common Values

ValueCountFrequency (%)
한국(韓國)-백제(百濟) 59
62.8%
한국(韓國)-청동기(靑銅器) 10
 
10.6%
한국(韓國)-초기철기(初期鐵器) 7
 
7.4%
한국(韓國)-고려(高麗) 5
 
5.3%
한국(韓國)-원삼국(原三國) 4
 
4.3%
한국(韓國)-조선(朝鮮) 2
 
2.1%
한국(韓國)-원삼국(原三國), 백제(百濟) 1
 
1.1%
백제 1
 
1.1%
한국(韓國) - 백제(百濟) 1
 
1.1%
한국(韓國)-통일신라(統一新羅) 1
 
1.1%
Other values (3) 3
 
3.2%

Length

2023-12-12T22:33:44.084070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한국(韓國)-백제(百濟 59
60.8%
한국(韓國)-청동기(靑銅器 10
 
10.3%
한국(韓國)-초기철기(初期鐵器 7
 
7.2%
한국(韓國)-고려(高麗 5
 
5.2%
한국(韓國)-원삼국(原三國 5
 
5.2%
한국(韓國)-조선(朝鮮 2
 
2.1%
백제(百濟 2
 
2.1%
백제 1
 
1.0%
한국(韓國 1
 
1.0%
1
 
1.0%
Other values (4) 4
 
4.1%

재질
Categorical

Distinct31
Distinct (%)33.0%
Missing0
Missing (%)0.0%
Memory size884.0 B
토제-경질
15 
토제-연질
11 
금속-금동
10 
금속-동합금
7 
석-화강암
7 
Other values (26)
44 

Length

Max length10
Median length5
Mean length4.8829787
Min length1

Unique

Unique18 ?
Unique (%)19.1%

Sample

1st row금속-동합금
2nd row유리보석-유리
3rd row토제-연질
4th row토제-연질
5th row유리보석-옥

Common Values

ValueCountFrequency (%)
토제-경질 15
16.0%
토제-연질 11
11.7%
금속-금동 10
10.6%
금속-동합금 7
 
7.4%
석-화강암 7
 
7.4%
금속-철 5
 
5.3%
석-기타 5
 
5.3%
토제 4
 
4.3%
토제-소조 4
 
4.3%
유리보석-옥 2
 
2.1%
Other values (21) 24
25.5%

Length

2023-12-12T22:33:44.222981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
토제-경질 15
14.9%
토제-연질 11
 
10.9%
금속-금동 10
 
9.9%
금속-동합금 7
 
6.9%
석-화강암 7
 
6.9%
토제 6
 
5.9%
금속-철 5
 
5.0%
석-기타 5
 
5.0%
토제-소조 4
 
4.0%
금속 3
 
3.0%
Other values (22) 28
27.7%

출토지
Text

MISSING 

Distinct56
Distinct (%)64.4%
Missing7
Missing (%)7.4%
Memory size884.0 B
2023-12-12T22:33:44.522692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length10.793103
Min length3

Characters and Unicode

Total characters939
Distinct characters86
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)48.3%

Sample

1st row예산군 대흥면 동서리
2nd row부여군 규암면 합송리
3rd row부여군 초촌면 송국리
4th row서산 해미면 휴암리
5th row부여군 초촌면 송국리
ValueCountFrequency (%)
부여군 59
23.4%
부여읍 31
 
12.3%
규암면 14
 
5.6%
능산리사지 10
 
4.0%
외리 8
 
3.2%
부소산 6
 
2.4%
부여 6
 
2.4%
초촌면 5
 
2.0%
서천군 4
 
1.6%
논산시 4
 
1.6%
Other values (74) 105
41.7%
2023-12-12T22:33:44.994801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
166
17.7%
부 105
 
11.2%
여 96
 
10.2%
군 72
 
7.7%
리 66
 
7.0%
산 39
 
4.2%
면 37
 
3.9%
읍 33
 
3.5%
지 22
 
2.3%
사 20
 
2.1%
Other values (76) 283
30.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 771
82.1%
Space Separator 166
 
17.7%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 105
 
13.6%
여 96
 
12.5%
군 72
 
9.3%
리 66
 
8.6%
산 39
 
5.1%
면 37
 
4.8%
읍 33
 
4.3%
지 22
 
2.9%
사 20
 
2.6%
암 16
 
2.1%
Other values (74) 265
34.4%
Space Separator
ValueCountFrequency (%)
166
100.0%
Other Punctuation
ValueCountFrequency (%)
· 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 771
82.1%
Common 168
 
17.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 105
 
13.6%
여 96
 
12.5%
군 72
 
9.3%
리 66
 
8.6%
산 39
 
5.1%
면 37
 
4.8%
읍 33
 
4.3%
지 22
 
2.9%
사 20
 
2.6%
암 16
 
2.1%
Other values (74) 265
34.4%
Common
ValueCountFrequency (%)
166
98.8%
· 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 771
82.1%
ASCII 166
 
17.7%
None 2
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
166
100.0%
Hangul
ValueCountFrequency (%)
부 105
 
13.6%
여 96
 
12.5%
군 72
 
9.3%
리 66
 
8.6%
산 39
 
5.1%
면 37
 
4.8%
읍 33
 
4.3%
지 22
 
2.9%
사 20
 
2.6%
암 16
 
2.1%
Other values (74) 265
34.4%
None
ValueCountFrequency (%)
· 2
100.0%

전시실
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size884.0 B
제1전시실
26 
제2전시실
24 
제3전시실
24 
기증유물실
11 
야외전시
7 

Length

Max length5
Median length5
Mean length4.9255319
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row제1전시실
2nd row제1전시실
3rd row제1전시실
4th row제1전시실
5th row제1전시실

Common Values

ValueCountFrequency (%)
제1전시실 26
27.7%
제2전시실 24
25.5%
제3전시실 24
25.5%
기증유물실 11
11.7%
야외전시 7
 
7.4%
전시실로비 2
 
2.1%

Length

2023-12-12T22:33:45.185295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:33:45.316771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제1전시실 26
27.7%
제2전시실 24
25.5%
제3전시실 24
25.5%
기증유물실 11
11.7%
야외전시 7
 
7.4%
전시실로비 2
 
2.1%

Interactions

2023-12-12T22:33:41.495769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:33:45.397901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호유물명유물번호국적/시대재질출토지전시실
번호1.0000.9711.0000.7000.7340.9480.922
유물명0.9711.0001.0000.9820.9841.0001.000
유물번호1.0001.0001.0001.0001.0001.0001.000
국적/시대0.7000.9821.0001.0000.8790.9760.830
재질0.7340.9841.0000.8791.0000.8090.803
출토지0.9481.0001.0000.9760.8091.0000.994
전시실0.9221.0001.0000.8300.8030.9941.000
2023-12-12T22:33:45.510616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
국적/시대재질전시실
국적/시대1.0000.4500.578
재질0.4501.0000.429
전시실0.5780.4291.000
2023-12-12T22:33:45.595352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호국적/시대재질전시실
번호1.0000.3730.3070.786
국적/시대0.3731.0000.4500.578
재질0.3070.4501.0000.429
전시실0.7860.5780.4291.000

Missing values

2023-12-12T22:33:41.606161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:33:41.735002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T22:33:41.850080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

번호유물명유물번호국적/시대재질출토지전시실
01대쪽모양 동기부여(扶餘)-002299한국(韓國)-초기철기(初期鐵器)금속-동합금예산군 대흥면 동서리제1전시실
12유리 대롱옥부여(扶餘)-003390, 003385한국(韓國)-초기철기(初期鐵器)유리보석-유리부여군 규암면 합송리제1전시실
23송국리식토기부여(扶餘)-002139한국(韓國)-청동기(靑銅器)토제-연질부여군 초촌면 송국리제1전시실
34서산 휴암리유적 출토 민무늬 토기·골아가리 토기신수(新收)-010887한국(韓國)-청동기(靑銅器)토제-연질서산 해미면 휴암리제1전시실
45대롱옥부여(扶餘)-002138한국(韓國)-청동기(靑銅器)유리보석-옥부여군 초촌면 송국리제1전시실
56홈자귀와 돌도끼신수(新收)-010550한국(韓國)-청동기(靑銅器)석제부여군 초촌면 송국리제1전시실
67삼각모양돌칼부여(扶餘)-005154한국(韓國)-청동기(靑銅器)석-점판암 석-사암부여군 초촌면 송국리제1전시실
78논산 마전리유적 우물출토 송국리식 토기부여(扶餘)-015960한국(韓國)-청동기(靑銅器)토제-연질논산시 연무읍 마전리제1전시실
89충남지역 출토 간돌검부여(扶餘)-003051한국(韓國)-청동기(靑銅器)석-점판암충남지역제1전시실
910검은간토기부여(扶餘)-002304한국(韓國)-초기철기(初期鐵器)토제-연질예산군 대흥면 동서리제1전시실
번호유물명유물번호국적/시대재질출토지전시실
8485손잡이단지부여(扶餘)-003764한국(韓國)-백제(百濟)토제-경질<NA>기증유물실
8586부여석조부여(扶餘)-000367한국(韓國)-백제(百濟)석-화강암부여군 부여읍 관북리 추정왕궁터전시실로비
8687백호<NA>한국(韓國)-광복이후(光復以後)지-기타부여군 부여읍 능산리고분전시실로비
8788당 유인원 기공비부여(扶餘)-000402한국(韓國)-백제(百濟)석-기타부여군 부여읍 부소산야외전시
8889박물관석조여래입상부여(扶餘)-000373한국(韓國)-고려(高麗)석-화강암부여군 부여읍 동남리 금성산야외전시
8990오층석탑부여(扶餘)-000377한국(韓國)-고려(高麗)석-화강암부여군 부여읍 석목리야외전시
9091부여보광사지대보광선사비부여(扶餘)-001628한국(韓國)-고려(高麗)석-기타부여군 임천면 가신리 보광사터야외전시
9192동사리 석탑<NA>한국(韓國)-고려(高麗)석-기타부여군 세도면 동사리야외전시
9293성주사지 출토 비머리부여(扶餘)-000411한국(韓國)-통일신라석-화강암충남 보령 성주사지야외전시
9394비석받침부여(扶餘)-001619한국(韓國)-통일산리석-화강암충남 보령 성주사지야외전시