Overview

Dataset statistics

Number of variables26
Number of observations996
Missing cells25891
Missing cells (%)> 99.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory202.4 KiB
Average record size in memory208.1 B

Variable types

Categorical5
Unsupported21

Alerts

ชื่อเรื่อง has constant value "ยุทธศาสตร์การพัฒนาระบบราชการ พ.ศ. 2567-2570 ฉบับคณะรัฐมนตรีมีมติเห็นชอบในหลักการ เมื่อวันที่ 9 กรกฎาคม 2567" Constant
รายละเอียด has constant value "มีข้อมูลรายละเอียดของแผนฯ คือ ยุทธศาสตร์ กลยุทธ์ แนวทาง เป้าหมาย ตัวชี้วัด " Constant
ปีที่เริ่มแผน has constant value "2567.0" Constant
ปีที่สิ้นสุดแผน has constant value "2570.0" Constant
URL ไฟล์เล่มแผน has constant value "https://www.opdc.go.th/wp-content/uploads/2025/02/Government_Administration_Development_Strategy67-70.pdf" Constant
ชื่อเรื่อง has 995 (99.9%) missing values Missing
รายละเอียด has 995 (99.9%) missing values Missing
ปีที่เริ่มแผน has 995 (99.9%) missing values Missing
ปีที่สิ้นสุดแผน has 995 (99.9%) missing values Missing
URL ไฟล์เล่มแผน has 995 (99.9%) missing values Missing
Unnamed: 5 has 996 (100.0%) missing values Missing
Unnamed: 6 has 996 (100.0%) missing values Missing
Unnamed: 7 has 996 (100.0%) missing values Missing
Unnamed: 8 has 996 (100.0%) missing values Missing
Unnamed: 9 has 996 (100.0%) missing values Missing
Unnamed: 10 has 996 (100.0%) missing values Missing
Unnamed: 11 has 996 (100.0%) missing values Missing
Unnamed: 12 has 996 (100.0%) missing values Missing
Unnamed: 13 has 996 (100.0%) missing values Missing
Unnamed: 14 has 996 (100.0%) missing values Missing
Unnamed: 15 has 996 (100.0%) missing values Missing
Unnamed: 16 has 996 (100.0%) missing values Missing
Unnamed: 17 has 996 (100.0%) missing values Missing
Unnamed: 18 has 996 (100.0%) missing values Missing
Unnamed: 19 has 996 (100.0%) missing values Missing
Unnamed: 20 has 996 (100.0%) missing values Missing
Unnamed: 21 has 996 (100.0%) missing values Missing
Unnamed: 22 has 996 (100.0%) missing values Missing
Unnamed: 23 has 996 (100.0%) missing values Missing
Unnamed: 24 has 996 (100.0%) missing values Missing
Unnamed: 25 has 996 (100.0%) missing values Missing
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 14 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 15 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 16 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 17 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 18 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 19 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 20 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 21 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 22 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 23 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 24 is an unsupported type, check if it needs cleaning or further analysis Unsupported
Unnamed: 25 is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2026-05-17 10:02:42.234561
Analysis finished2026-05-17 10:02:45.105954
Duration2.87 seconds
Software versionpandas-profiling v3.1.0
Download configurationconfig.json

Variables

ชื่อเรื่อง
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing995
Missing (%)99.9%
Memory size7.9 KiB
ยุทธศาสตร์การพัฒนาระบบราชการ พ.ศ. 2567-2570 ฉบับคณะรัฐมนตรีมีมติเห็นชอบในหลักการ เมื่อวันที่ 9 กรกฎาคม 2567

Length

Max length107
Median length107
Mean length107
Min length107

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowยุทธศาสตร์การพัฒนาระบบราชการ พ.ศ. 2567-2570 ฉบับคณะรัฐมนตรีมีมติเห็นชอบในหลักการ เมื่อวันที่ 9 กรกฎาคม 2567

Common Values

ValueCountFrequency (%)
ยุทธศาสตร์การพัฒนาระบบราชการ พ.ศ. 2567-2570 ฉบับคณะรัฐมนตรีมีมติเห็นชอบในหลักการ เมื่อวันที่ 9 กรกฎาคม 25671
 
0.1%
(Missing)995
99.9%

Length

2026-05-17T17:02:45.176434image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2026-05-17T17:02:45.261896image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
25671
12.5%
กรกฎาคม1
12.5%
91
12.5%
เมื่อวันที่1
12.5%
ฉบับคณะรัฐมนตรีมีมติเห็นชอบในหลักการ1
12.5%
2567-25701
12.5%
พ.ศ1
12.5%
ยุทธศาสตร์การพัฒนาระบบราชการ1
12.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

รายละเอียด
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing995
Missing (%)99.9%
Memory size7.9 KiB
มีข้อมูลรายละเอียดของแผนฯ คือ ยุทธศาสตร์ กลยุทธ์ แนวทาง เป้าหมาย ตัวชี้วัด 

Length

Max length75
Median length75
Mean length75
Min length75

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowมีข้อมูลรายละเอียดของแผนฯ คือ ยุทธศาสตร์ กลยุทธ์ แนวทาง เป้าหมาย ตัวชี้วัด 

Common Values

ValueCountFrequency (%)
มีข้อมูลรายละเอียดของแผนฯ คือ ยุทธศาสตร์ กลยุทธ์ แนวทาง เป้าหมาย ตัวชี้วัด 1
 
0.1%
(Missing)995
99.9%

Length

2026-05-17T17:02:45.353796image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2026-05-17T17:02:45.439538image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
ตัวชี้วัด1
14.3%
เป้าหมาย1
14.3%
แนวทาง1
14.3%
กลยุทธ์1
14.3%
ยุทธศาสตร์1
14.3%
คือ1
14.3%
มีข้อมูลรายละเอียดของแผนฯ1
14.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

ปีที่เริ่มแผน
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing995
Missing (%)99.9%
Memory size7.9 KiB
2567.0

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2567.0

Common Values

ValueCountFrequency (%)
2567.01
 
0.1%
(Missing)995
99.9%

Length

2026-05-17T17:02:45.528656image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2026-05-17T17:02:45.613062image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
2567.01
100.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

ปีที่สิ้นสุดแผน
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing995
Missing (%)99.9%
Memory size7.9 KiB
2570.0

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row2570.0

Common Values

ValueCountFrequency (%)
2570.01
 
0.1%
(Missing)995
99.9%

Length

2026-05-17T17:02:45.695642image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2026-05-17T17:02:45.780374image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
2570.01
100.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

URL ไฟล์เล่มแผน
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing995
Missing (%)99.9%
Memory size7.9 KiB
https://www.opdc.go.th/wp-content/uploads/2025/02/Government_Administration_Development_Strategy67-70.pdf

Length

Max length105
Median length105
Mean length105
Min length105

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowhttps://www.opdc.go.th/wp-content/uploads/2025/02/Government_Administration_Development_Strategy67-70.pdf

Common Values

ValueCountFrequency (%)
https://www.opdc.go.th/wp-content/uploads/2025/02/Government_Administration_Development_Strategy67-70.pdf1
 
0.1%
(Missing)995
99.9%

Length

2026-05-17T17:02:45.863045image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2026-05-17T17:02:45.948518image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
https://www.opdc.go.th/wp-content/uploads/2025/02/government_administration_development_strategy67-70.pdf1
100.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Unnamed: 5
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 6
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 7
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 8
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 9
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 10
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 11
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 12
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 13
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 14
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 15
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 16
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 17
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 18
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 19
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 20
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 21
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 22
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 23
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 24
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Unnamed: 25
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing996
Missing (%)100.0%
Memory size7.9 KiB

Correlations

2026-05-17T17:02:46.071736image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2026-05-17T17:02:46.479308image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2026-05-17T17:02:47.038079image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2026-05-17T17:02:47.408033image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2026-05-17T17:02:43.187420image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
A simple visualization of nullity by column.
2026-05-17T17:02:44.340443image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2026-05-17T17:02:44.659075image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2026-05-17T17:02:44.873969image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

ชื่อเรื่องรายละเอียดปีที่เริ่มแผนปีที่สิ้นสุดแผนURL ไฟล์เล่มแผนUnnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25
0ยุทธศาสตร์การพัฒนาระบบราชการ พ.ศ. 2567-2570 ฉบับคณะรัฐมนตรีมีมติเห็นชอบในหลักการ เมื่อวันที่ 9 กรกฎาคม 2567มีข้อมูลรายละเอียดของแผนฯ คือ ยุทธศาสตร์ กลยุทธ์ แนวทาง เป้าหมาย ตัวชี้วัด2567.02570.0https://www.opdc.go.th/wp-content/uploads/2025/02/Government_Administration_Development_Strategy67-70.pdfNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
2NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
3NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
4NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
5NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
6NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
7NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
8NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
9NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN

Last rows

ชื่อเรื่องรายละเอียดปีที่เริ่มแผนปีที่สิ้นสุดแผนURL ไฟล์เล่มแผนUnnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25
986NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
987NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
988NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
989NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
990NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
991NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
992NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
993NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
994NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
995NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN