Overview

Brought to you by YData

Dataset statistics

Number of variables5
Number of observations189
Missing cells188
Missing cells (%)19.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.5 KiB
Average record size in memory40.7 B

Variable types

URL1
Categorical2
DateTime1
Text1

Alerts

notes has constant value "Reportedly blocked"Constant
source is highly imbalanced (81.6%)Imbalance
notes has 188 (99.5%) missing valuesMissing
url has unique valuesUnique

Reproduction

Analysis started2024-07-15 20:42:27.607559
Analysis finished2024-07-15 20:42:27.967049
Duration0.36 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

url
URL

UNIQUE 

Distinct189
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
http://abrahadesta.wordpress.com/
 
1
http://www.ocha-eth.org/
 
1
http://www.medhin.org/
 
1
http://www.mediaethiopia.com/
 
1
http://www.mediaethiopia.com/blog/
 
1
Other values (184)
184 
ValueCountFrequency (%)
http://abrahadesta.wordpress.com/ 1
 
0.5%
http://www.ocha-eth.org/ 1
 
0.5%
http://www.medhin.org/ 1
 
0.5%
http://www.mediaethiopia.com/ 1
 
0.5%
http://www.mediaethiopia.com/blog/ 1
 
0.5%
http://www.mereja.com/ 1
 
0.5%
http://www.mesfinwoldemariam.org/ 1
 
0.5%
http://www.meskelsquare.com/ 1
 
0.5%
http://www.nazret.com/ 1
 
0.5%
http://www.nazret.com/news/view_amharic.php?feed=5&how=paged&what=all 1
 
0.5%
Other values (179) 179
94.7%
ValueCountFrequency (%)
http 173
91.5%
https 16
 
8.5%
ValueCountFrequency (%)
nazret.com 8
 
4.2%
www.cafpde.org 3
 
1.6%
www.hrw.org 3
 
1.6%
www.ethpress.gov.et 2
 
1.1%
web.worldbank.org 2
 
1.1%
www.tzta.ca 2
 
1.1%
www.twitter.com 2
 
1.1%
www.aeup.org 2
 
1.1%
www.aigaforum.com 2
 
1.1%
www.torproject.org 2
 
1.1%
Other values (134) 161
85.2%
ValueCountFrequency (%)
/ 127
67.2%
/blog/index.php 7
 
3.7%
/index.html 2
 
1.1%
/index.htm 2
 
1.1%
/tzta/english.htm 1
 
0.5%
/doc 1
 
0.5%
/ethiopia/ 1
 
0.5%
/public/english/region/afpro/addisababa/ethiopia.htm 1
 
0.5%
/external/country/ETH/index.htm 1
 
0.5%
/research-publications/speaksafe-media-workers-toolkit-safer-online-and-mobile-practices 1
 
0.5%
Other values (45) 45
 
23.8%
ValueCountFrequency (%)
174
92.1%
blog=12 1
 
0.5%
blog=13 1
 
0.5%
blog=14 1
 
0.5%
blog=15 1
 
0.5%
blog=16 1
 
0.5%
blog=7 1
 
0.5%
blog=9 1
 
0.5%
c=ethiop&t=africa 1
 
0.5%
feed=5&how=paged&what=all 1
 
0.5%
Other values (6) 6
 
3.2%
ValueCountFrequency (%)
188
99.5%
ethiopia 1
 
0.5%

category_code
Categorical

Distinct15
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
NEWS
65 
HUMR
45 
POLR
32 
ECON
13 
ANON
8 
Other values (10)
26 

Length

Max length5
Median length4
Mean length4
Min length3

Characters and Unicode

Total characters756
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)2.1%

Sample

1st rowCULTR
2nd rowNEWS
3rd rowMISC
4th rowMISC
5th rowNEWS

Common Values

ValueCountFrequency (%)
NEWS 65
34.4%
HUMR 45
23.8%
POLR 32
16.9%
ECON 13
 
6.9%
ANON 8
 
4.2%
CULTR 7
 
3.7%
XED 5
 
2.6%
MISC 3
 
1.6%
HOST 3
 
1.6%
MILX 2
 
1.1%
Other values (5) 6
 
3.2%

Length

2024-07-15T20:42:28.091529image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
news 65
34.4%
humr 45
23.8%
polr 32
16.9%
econ 13
 
6.9%
anon 8
 
4.2%
cultr 7
 
3.7%
xed 5
 
2.6%
misc 3
 
1.6%
host 3
 
1.6%
milx 2
 
1.1%
Other values (5) 6
 
3.2%

Most occurring characters

ValueCountFrequency (%)
N 95
12.6%
R 86
11.4%
E 85
11.2%
S 72
9.5%
W 65
8.6%
O 56
7.4%
U 54
7.1%
H 51
6.7%
M 50
6.6%
L 42
5.6%
Other values (11) 100
13.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 756
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 95
12.6%
R 86
11.4%
E 85
11.2%
S 72
9.5%
W 65
8.6%
O 56
7.4%
U 54
7.1%
H 51
6.7%
M 50
6.6%
L 42
5.6%
Other values (11) 100
13.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 756
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 95
12.6%
R 86
11.4%
E 85
11.2%
S 72
9.5%
W 65
8.6%
O 56
7.4%
U 54
7.1%
H 51
6.7%
M 50
6.6%
L 42
5.6%
Other values (11) 100
13.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 756
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 95
12.6%
R 86
11.4%
E 85
11.2%
S 72
9.5%
W 65
8.6%
O 56
7.4%
U 54
7.1%
H 51
6.7%
M 50
6.6%
L 42
5.6%
Other values (11) 100
13.2%

date_added
Date

Distinct6
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2014-04-15 00:00:00
Maximum2018-04-10 00:00:00
2024-07-15T20:42:28.257181image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-07-15T20:42:28.395849image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)

source
Categorical

IMBALANCE 

Distinct5
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
citizenlab
178 
CIPIT
 
4
OONI
 
4
BBC
 
2
defenddefenders
 
1

Length

Max length15
Median length10
Mean length9.7195767
Min length3

Characters and Unicode

Total characters1837
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
citizenlab 178
94.2%
CIPIT 4
 
2.1%
OONI 4
 
2.1%
BBC 2
 
1.1%
defenddefenders 1
 
0.5%

Length

2024-07-15T20:42:28.526806image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-15T20:42:28.647679image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
ValueCountFrequency (%)
citizenlab 178
94.2%
cipit 4
 
2.1%
ooni 4
 
2.1%
bbc 2
 
1.1%
defenddefenders 1
 
0.5%

Most occurring characters

ValueCountFrequency (%)
i 356
19.4%
e 183
10.0%
n 180
9.8%
c 178
9.7%
t 178
9.7%
z 178
9.7%
l 178
9.7%
a 178
9.7%
b 178
9.7%
I 12
 
0.7%
Other values (10) 38
 
2.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1837
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 356
19.4%
e 183
10.0%
n 180
9.8%
c 178
9.7%
t 178
9.7%
z 178
9.7%
l 178
9.7%
a 178
9.7%
b 178
9.7%
I 12
 
0.7%
Other values (10) 38
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1837
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 356
19.4%
e 183
10.0%
n 180
9.8%
c 178
9.7%
t 178
9.7%
z 178
9.7%
l 178
9.7%
a 178
9.7%
b 178
9.7%
I 12
 
0.7%
Other values (10) 38
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1837
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 356
19.4%
e 183
10.0%
n 180
9.8%
c 178
9.7%
t 178
9.7%
z 178
9.7%
l 178
9.7%
a 178
9.7%
b 178
9.7%
I 12
 
0.7%
Other values (10) 38
 
2.1%

notes
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing188
Missing (%)99.5%
Memory size1.6 KiB
2024-07-15T20:42:28.775292image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters18
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 rowReportedly blocked
ValueCountFrequency (%)
reportedly 1
50.0%
blocked 1
50.0%
2024-07-15T20:42:29.014091image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 3
16.7%
o 2
11.1%
d 2
11.1%
l 2
11.1%
R 1
 
5.6%
p 1
 
5.6%
r 1
 
5.6%
t 1
 
5.6%
y 1
 
5.6%
1
 
5.6%
Other values (3) 3
16.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 18
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 3
16.7%
o 2
11.1%
d 2
11.1%
l 2
11.1%
R 1
 
5.6%
p 1
 
5.6%
r 1
 
5.6%
t 1
 
5.6%
y 1
 
5.6%
1
 
5.6%
Other values (3) 3
16.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 18
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 3
16.7%
o 2
11.1%
d 2
11.1%
l 2
11.1%
R 1
 
5.6%
p 1
 
5.6%
r 1
 
5.6%
t 1
 
5.6%
y 1
 
5.6%
1
 
5.6%
Other values (3) 3
16.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 18
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 3
16.7%
o 2
11.1%
d 2
11.1%
l 2
11.1%
R 1
 
5.6%
p 1
 
5.6%
r 1
 
5.6%
t 1
 
5.6%
y 1
 
5.6%
1
 
5.6%
Other values (3) 3
16.7%

Correlations

2024-07-15T20:42:29.183857image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
category_codesource
category_code1.0000.100
source0.1001.000

Missing values

2024-07-15T20:42:27.747197image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-07-15T20:42:27.903038image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

urlcategory_codedate_addedsourcenotes
0http://abrahadesta.wordpress.com/CULTR2014-04-15citizenlabNaN
1http://aljazeera.net/NEWS2014-04-15citizenlabNaN
2http://am.wikipedia.org/MISC2014-04-15citizenlabNaN
3http://am.wikipedia.org/wiki/%E1%8B%8B%E1%8A%93%E1%8B%8D_%E1%8C%88%E1%8C%BDMISC2014-04-15citizenlabNaN
4http://amharic.voanews.com/NEWS2014-04-15citizenlabNaN
5http://ancientgebts.org/HUMR2014-04-15citizenlabNaN
6http://carpediemethiopia.blogspot.com/POLR2014-04-15citizenlabNaN
7http://citizenlab.org/NEWS2014-04-15citizenlabNaN
8http://cpj.org/NEWS2014-04-15citizenlabNaN
9http://egoportal.blogspot.com/POLR2014-04-15citizenlabNaN
urlcategory_codedate_addedsourcenotes
179https://www.citizenlab.org/NEWS2014-04-15citizenlabNaN
180https://www.dropbox.com/s/n65b3d67f82asn2/Leaked%20National%20Entrance%20Exam_English.pdf?dl=0FILE2016-05-30OONINaN
181https://www.facebook.com/JawarmdNEWS2016-05-30OONINaN
182https://www.facebook.com/pages/Addis-Neger/49967100821NEWS2014-04-15citizenlabNaN
183https://www.hrw.org/HUMR2014-04-15citizenlabNaN
184https://www.mereja.com/NEWS2016-09-09CIPITNaN
185https://www.oromiamedia.org/NEWS2016-05-30OONINaN
186https://www.privacyinternational.org/HUMR2014-04-15citizenlabNaN
187https://www.torproject.org/NEWS2014-04-15citizenlabNaN
188https://www.twitter.com/HOST2014-04-15citizenlabNaN