gimi9 Pandas Profiling

Dataset statistics

Number of variables	14
Number of observations	51
Missing cells	51
Missing cells (%)	7.1%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	6.4 KiB
Average record size in memory	127.5 B

Variable types

Categorical	7
Unsupported	1
Numeric	6

Dataset

Description	기타 가축통계(메추리)
Author	농림축산식품부
URL	https://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220216000000001951

Alerts

`ORDR` has 51 (100.0%) missing values	Missing
`ORDR` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`BRD_FRNTR_CO_SM` has 9 (17.6%) zeros	Zeros
`N1000FR_N9999FR` has 40 (78.4%) zeros	Zeros
`N20000FR_N29999FR` has 35 (68.6%) zeros	Zeros
`N30000FR_N39999FR` has 33 (64.7%) zeros	Zeros
`N50000FR_N99999FR` has 22 (43.1%) zeros	Zeros
`N100000FR_ABOVE` has 29 (56.9%) zeros	Zeros

Reproduction

Analysis started	2022-08-12 14:44:47.526415
Analysis finished	2022-08-12 14:44:56.075965
Duration	8.55 seconds
Software version	pandas-profiling v3.2.0
Download configuration	config.json

YEAR
Categorical

Distinct	3
Distinct (%)	5.9%
Missing	0
Missing (%)	0.0%
Memory size	536.0 B

2015	17
2013	17
2014	17

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2015
2nd row	2015
3rd row	2015
4th row	2015
5th row	2015

Common Values

Value	Count	Frequency (%)
2015	17	33.3%
2013	17	33.3%
2014	17	33.3%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
2015	17	33.3%
2013	17	33.3%
2014	17	33.3%

ORDR
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	51
Missing (%)	100.0%
Memory size	587.0 B

YEAR_AREA
Categorical

Distinct	17
Distinct (%)	33.3%
Missing	0
Missing (%)	0.0%
Memory size	536.0 B

서울	3
부산	3
대구	3
인천	3
광주	3
Other values (12)	36

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	서울
2nd row	부산
3rd row	대구
4th row	인천
5th row	광주

Common Values

Value	Count	Frequency (%)
서울	3	5.9%
부산	3	5.9%
대구	3	5.9%
인천	3	5.9%
광주	3	5.9%
대전	3	5.9%
울산	3	5.9%
경기	3	5.9%
강원	3	5.9%
충북	3	5.9%
Other values (7)	21	41.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
서울	3	5.9%
충북	3	5.9%
제주	3	5.9%
경남	3	5.9%
경북	3	5.9%
전남	3	5.9%
전북	3	5.9%
충남	3	5.9%
강원	3	5.9%
부산	3	5.9%
Other values (7)	21	41.2%

BRD_FRNTR_CO_SM
Real number (ℝ_≥0)

ZEROS

Distinct	18
Distinct (%)	35.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.078431373

Minimum	0
Maximum	44
Zeros	9
Zeros (%)	17.6%
Negative	0
Negative (%)	0.0%
Memory size	587.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	4
Q3	9
95-th percentile	25.5
Maximum	44
Range	44
Interquartile range (IQR)	8

Descriptive statistics

Standard deviation	9.234377374
Coefficient of variation (CV)	1.304579629
Kurtosis	7.108498436
Mean	7.078431373
Median Absolute Deviation (MAD)	4
Skewness	2.519445217
Sum	361
Variance	85.27372549
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=18)

Value	Count	Frequency (%)
0	9	17.6%
1	8	15.7%
8	5	9.8%
3	4	7.8%
9	4	7.8%
7	3	5.9%
2	3	5.9%
14	2	3.9%
4	2	3.9%
6	2	3.9%
Other values (8)	9	17.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	9	17.6%
1	8	15.7%
2	3	5.9%
3	4	7.8%
4	2	3.9%
6	2	3.9%
7	3	5.9%
8	5	9.8%
9	4	7.8%
10	2	3.9%

Value	Count	Frequency (%)
44	1	2.0%
37	1	2.0%
35	1	2.0%
16	1	2.0%
15	1	2.0%
14	2	3.9%
12	1	2.0%
11	1	2.0%
10	2	3.9%
9	4	7.8%

N1FR_N99FR
Categorical

Distinct	4
Distinct (%)	7.8%
Missing	0
Missing (%)	0.0%
Memory size	536.0 B

0	38
1	9
2	3
6	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Unique

Unique	1 ?
Unique (%)	2.0%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	38	74.5%
1	9	17.6%
2	3	5.9%
6	1	2.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	38	74.5%
1	9	17.6%
2	3	5.9%
6	1	2.0%

N100FR_N499FR
Categorical

Distinct	2
Distinct (%)	3.9%
Missing	0
Missing (%)	0.0%
Memory size	536.0 B

0	49
1	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	49	96.1%
1	2	3.9%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	49	96.1%
1	2	3.9%

N500FR_N999FR
Categorical

Distinct	2
Distinct (%)	3.9%
Missing	0
Missing (%)	0.0%
Memory size	536.0 B

0	49
1	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	49	96.1%
1	2	3.9%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	49	96.1%
1	2	3.9%

N1000FR_N9999FR
Real number (ℝ_≥0)

ZEROS

Distinct	6
Distinct (%)	11.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.4509803922

Minimum	0
Maximum	5
Zeros	40
Zeros (%)	78.4%
Negative	0
Negative (%)	0.0%
Memory size	587.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	2.5
Maximum	5
Range	5
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.064212864
Coefficient of variation (CV)	2.35977635
Kurtosis	8.212210261
Mean	0.4509803922
Median Absolute Deviation (MAD)	0
Skewness	2.827417903
Sum	23
Variance	1.13254902
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	40	78.4%
1	5	9.8%
2	3	5.9%
5	1	2.0%
3	1	2.0%
4	1	2.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	40	78.4%
1	5	9.8%
2	3	5.9%
3	1	2.0%
4	1	2.0%
5	1	2.0%

Value	Count	Frequency (%)
5	1	2.0%
4	1	2.0%
3	1	2.0%
2	3	5.9%
1	5	9.8%
0	40	78.4%

N10000FR_N19999FR
Categorical

Distinct	5
Distinct (%)	9.8%
Missing	0
Missing (%)	0.0%
Memory size	536.0 B

0	42
1	6
2	1
4	1
3	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Unique

Unique	3 ?
Unique (%)	5.9%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	42	82.4%
1	6	11.8%
2	1	2.0%
4	1	2.0%
3	1	2.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	42	82.4%
1	6	11.8%
2	1	2.0%
4	1	2.0%
3	1	2.0%

N20000FR_N29999FR
Real number (ℝ_≥0)

ZEROS

Distinct	6
Distinct (%)	11.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.7843137255

Minimum	0
Maximum	13
Zeros	35
Zeros (%)	68.6%
Negative	0
Negative (%)	0.0%
Memory size	587.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	1
95-th percentile	3
Maximum	13
Range	13
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	2.032867192
Coefficient of variation (CV)	2.59190567
Kurtosis	26.75072325
Mean	0.7843137255
Median Absolute Deviation (MAD)	0
Skewness	4.750585882
Sum	40
Variance	4.13254902
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	35	68.6%
1	9	17.6%
3	3	5.9%
2	2	3.9%
13	1	2.0%
5	1	2.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	35	68.6%
1	9	17.6%
2	2	3.9%
3	3	5.9%
5	1	2.0%
13	1	2.0%

Value	Count	Frequency (%)
13	1	2.0%
5	1	2.0%
3	3	5.9%
2	2	3.9%
1	9	17.6%
0	35	68.6%

N30000FR_N39999FR
Real number (ℝ_≥0)

ZEROS

Distinct	6
Distinct (%)	11.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.8823529412

Minimum	0
Maximum	12
Zeros	33
Zeros (%)	64.7%
Negative	0
Negative (%)	0.0%
Memory size	587.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	1
95-th percentile	3
Maximum	12
Range	12
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.935428209
Coefficient of variation (CV)	2.193485304
Kurtosis	21.74491222
Mean	0.8823529412
Median Absolute Deviation (MAD)	0
Skewness	4.13515443
Sum	45
Variance	3.745882353
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
0	33	64.7%
1	9	17.6%
3	6	11.8%
12	1	2.0%
4	1	2.0%
2	1	2.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	33	64.7%
1	9	17.6%
2	1	2.0%
3	6	11.8%
4	1	2.0%
12	1	2.0%

Value	Count	Frequency (%)
12	1	2.0%
4	1	2.0%
3	6	11.8%
2	1	2.0%
1	9	17.6%
0	33	64.7%

N40000FR_N49999FR
Categorical

Distinct	4
Distinct (%)	7.8%
Missing	0
Missing (%)	0.0%
Memory size	536.0 B

0	41
1	6
2	3
3	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Unique

Unique	1 ?
Unique (%)	2.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	41	80.4%
1	6	11.8%
2	3	5.9%
3	1	2.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	41	80.4%
1	6	11.8%
2	3	5.9%
3	1	2.0%

N50000FR_N99999FR
Real number (ℝ_≥0)

ZEROS

Distinct	8
Distinct (%)	15.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.823529412

Minimum	0
Maximum	16
Zeros	22
Zeros (%)	43.1%
Negative	0
Negative (%)	0.0%
Memory size	587.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	2
95-th percentile	4.5
Maximum	16
Range	16
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	3.057488396
Coefficient of variation (CV)	1.676687185
Kurtosis	13.0275689
Mean	1.823529412
Median Absolute Deviation (MAD)	1
Skewness	3.355078873
Sum	93
Variance	9.348235294
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
0	22	43.1%
2	9	17.6%
1	8	15.7%
4	5	9.8%
3	4	7.8%
14	1	2.0%
16	1	2.0%
5	1	2.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	22	43.1%
1	8	15.7%
2	9	17.6%
3	4	7.8%
4	5	9.8%
5	1	2.0%
14	1	2.0%
16	1	2.0%

Value	Count	Frequency (%)
16	1	2.0%
14	1	2.0%
5	1	2.0%
4	5	9.8%
3	4	7.8%
2	9	17.6%
1	8	15.7%
0	22	43.1%

N100000FR_ABOVE
Real number (ℝ_≥0)

ZEROS

Distinct	11
Distinct (%)	21.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.235294118

Minimum	0
Maximum	20
Zeros	29
Zeros (%)	56.9%
Negative	0
Negative (%)	0.0%
Memory size	587.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	3.5
95-th percentile	8
Maximum	20
Range	20
Interquartile range (IQR)	3.5

Descriptive statistics

Standard deviation	3.967811665
Coefficient of variation (CV)	1.77507364
Kurtosis	8.068666994
Mean	2.235294118
Median Absolute Deviation (MAD)	0
Skewness	2.583800086
Sum	114
Variance	15.74352941
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
0	29	56.9%
1	5	9.8%
2	3	5.9%
7	3	5.9%
4	3	5.9%
6	2	3.9%
8	2	3.9%
14	1	2.0%
3	1	2.0%
20	1	2.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	29	56.9%
1	5	9.8%
2	3	5.9%
3	1	2.0%
4	3	5.9%
5	1	2.0%
6	2	3.9%
7	3	5.9%
8	2	3.9%
14	1	2.0%

Value	Count	Frequency (%)
20	1	2.0%
14	1	2.0%
8	2	3.9%
7	3	5.9%
6	2	3.9%
5	1	2.0%
4	3	5.9%
3	1	2.0%
2	3	5.9%
1	5	9.8%

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.

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.

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.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

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.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	YEAR	ORDR	YEAR_AREA	BRD_FRNTR_CO_SM	N1FR_N99FR	N500FR_N999FR	N1000FR_N9999FR	N10000FR_N19999FR	N20000FR_N29999FR	N30000FR_N39999FR	N40000FR_N49999FR	N50000FR_N99999FR	N100000FR_ABOVE
0	2015	<NA>	서울	1	1	0	0	0	0	0	0	0	0
1	2015	<NA>	부산	0	0	0	0	0	0	0	0	0	0
2	2015	<NA>	대구	1	0	0	0	0	1	0	0	0	0
3	2015	<NA>	인천	3	0	0	0	0	3	0	0	0	0
4	2015	<NA>	광주	3	0	0	1	1	1	0	0	0	0
5	2015	<NA>	대전	0	0	0	0	0	0	0	0	0	0
6	2015	<NA>	울산	0	0	0	0	0	0	0	0	0	0
7	2015	<NA>	경기	35	0	1	0	2	13	12	3	2	2
8	2015	<NA>	강원	6	2	0	0	1	1	1	0	1	0
9	2015	<NA>	충북	15	1	0	2	0	5	3	2	1	1

Last rows

	YEAR	ORDR	YEAR_AREA	BRD_FRNTR_CO_SM	N1FR_N99FR	N1000FR_N9999FR	N20000FR_N29999FR	N30000FR_N39999FR	N40000FR_N49999FR	N50000FR_N99999FR	N100000FR_ABOVE
41	2014	<NA>	경기	44	0	2	1	3	2	16	20
42	2014	<NA>	강원	7	2	1	0	0	0	2	2
43	2014	<NA>	충북	14	0	0	0	2	0	5	7
44	2014	<NA>	충남	9	0	0	0	0	0	3	6
45	2014	<NA>	전북	8	0	0	0	0	0	0	8
46	2014	<NA>	전남	8	0	0	0	1	0	3	4
47	2014	<NA>	경북	11	0	4	0	0	1	2	4
48	2014	<NA>	경남	10	1	0	0	0	0	4	5
49	2014	<NA>	제주	1	0	0	0	0	0	0	1
50	2014	<NA>	세종	2	0	0	0	0	0	2	0

Overview

Variables

Common Values

Length

Category Frequency Plot

Common Values

Length

Common Values

Length

Category Frequency Plot

Common Values

Length

Category Frequency Plot

Common Values

Length

Category Frequency Plot

Common Values

Length

Category Frequency Plot

Common Values

Length

Category Frequency Plot

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows