Overview

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 started2026-01-13 18:40:49.100121
Analysis finished2026-01-13 18:40:49.297549
Duration0.2 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://aljazeera.net/
 
1
http://am.wikipedia.org/
 
1
http://am.wikipedia.org/wiki/%E1%8B%8B%E1%8A%93%E1%8B%8D_%E1%8C%88%E1%8C%BD
 
1
http://amharic.voanews.com/
 
1
Other values (184)
184 
ValueCountFrequency (%)
http://abrahadesta.wordpress.com/1
 
0.5%
http://aljazeera.net/1
 
0.5%
http://am.wikipedia.org/1
 
0.5%
http://am.wikipedia.org/wiki/%E1%8B%8B%E1%8A%93%E1%8B%8D_%E1%8C%88%E1%8C%BD1
 
0.5%
http://amharic.voanews.com/1
 
0.5%
http://ancientgebts.org/1
 
0.5%
http://carpediemethiopia.blogspot.com/1
 
0.5%
http://citizenlab.org/1
 
0.5%
http://cpj.org/1
 
0.5%
http://egoportal.blogspot.com/1
 
0.5%
Other values (179)179
94.7%
ValueCountFrequency (%)
http173
91.5%
https16
 
8.5%
ValueCountFrequency (%)
nazret.com8
 
4.2%
www.cafpde.org3
 
1.6%
www.hrw.org3
 
1.6%
am.wikipedia.org2
 
1.1%
www.awate.com2
 
1.1%
citizenlab.org2
 
1.1%
facebook.com2
 
1.1%
www.ethiopiafirst.com2
 
1.1%
portal.unesco.org2
 
1.1%
www.aigaforum.com2
 
1.1%
Other values (134)161
85.2%
ValueCountFrequency (%)
/127
67.2%
/blog/index.php7
 
3.7%
/index.html2
 
1.1%
/index.htm2
 
1.1%
/story/201306250132-00228541
 
0.5%
/geography/en/ev.php-URL_ID=3559&URL_DO=DO_TOPIC&URL_SECTION=201.html1
 
0.5%
/wiki/%E1%8B%8B%E1%8A%93%E1%8B%8D_%E1%8C%88%E1%8C%BD1
 
0.5%
/library/eng-eth/index1
 
0.5%
/~ena/1
 
0.5%
/new/index.asp1
 
0.5%
Other values (45)45
 
23.8%
ValueCountFrequency (%)
174
92.1%
blog=121
 
0.5%
blog=131
 
0.5%
blog=141
 
0.5%
blog=151
 
0.5%
blog=161
 
0.5%
blog=71
 
0.5%
blog=91
 
0.5%
c=ethiop&t=africa1
 
0.5%
feed=5&how=paged&what=all1
 
0.5%
Other values (6)6
 
3.2%
ValueCountFrequency (%)
188
99.5%
ethiopia1
 
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 (%)
NEWS65
34.4%
HUMR45
23.8%
POLR32
16.9%
ECON13
 
6.9%
ANON8
 
4.2%
CULTR7
 
3.7%
XED5
 
2.6%
MISC3
 
1.6%
HOST3
 
1.6%
PUBH2
 
1.1%
Other values (5)6
 
3.2%

Length

2026-01-13T18:40:49.352495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
news65
34.4%
humr45
23.8%
polr32
16.9%
econ13
 
6.9%
anon8
 
4.2%
cultr7
 
3.7%
xed5
 
2.6%
misc3
 
1.6%
host3
 
1.6%
pubh2
 
1.1%
Other values (5)6
 
3.2%

Most occurring characters

ValueCountFrequency (%)
N95
12.6%
R86
11.4%
E85
11.2%
S72
9.5%
W65
8.6%
O56
7.4%
U54
7.1%
H51
6.7%
M50
6.6%
L42
5.6%
Other values (11)100
13.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)756
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N95
12.6%
R86
11.4%
E85
11.2%
S72
9.5%
W65
8.6%
O56
7.4%
U54
7.1%
H51
6.7%
M50
6.6%
L42
5.6%
Other values (11)100
13.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)756
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N95
12.6%
R86
11.4%
E85
11.2%
S72
9.5%
W65
8.6%
O56
7.4%
U54
7.1%
H51
6.7%
M50
6.6%
L42
5.6%
Other values (11)100
13.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)756
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N95
12.6%
R86
11.4%
E85
11.2%
S72
9.5%
W65
8.6%
O56
7.4%
U54
7.1%
H51
6.7%
M50
6.6%
L42
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
Invalid dates0
Invalid dates (%)0.0%
2026-01-13T18:40:49.420178image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-13T18:40:49.489810image/svg+xmlMatplotlib v3.10.0, 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 
OONI
 
4
CIPIT
 
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 (%)
citizenlab178
94.2%
OONI4
 
2.1%
CIPIT4
 
2.1%
BBC2
 
1.1%
defenddefenders1
 
0.5%

Length

2026-01-13T18:40:49.565001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2026-01-13T18:40:49.622122image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
citizenlab178
94.2%
ooni4
 
2.1%
cipit4
 
2.1%
bbc2
 
1.1%
defenddefenders1
 
0.5%

Most occurring characters

ValueCountFrequency (%)
i356
19.4%
e183
10.0%
n180
9.8%
c178
9.7%
z178
9.7%
t178
9.7%
l178
9.7%
a178
9.7%
b178
9.7%
I12
 
0.7%
Other values (10)38
 
2.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)1837
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i356
19.4%
e183
10.0%
n180
9.8%
c178
9.7%
z178
9.7%
t178
9.7%
l178
9.7%
a178
9.7%
b178
9.7%
I12
 
0.7%
Other values (10)38
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1837
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i356
19.4%
e183
10.0%
n180
9.8%
c178
9.7%
z178
9.7%
t178
9.7%
l178
9.7%
a178
9.7%
b178
9.7%
I12
 
0.7%
Other values (10)38
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1837
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i356
19.4%
e183
10.0%
n180
9.8%
c178
9.7%
z178
9.7%
t178
9.7%
l178
9.7%
a178
9.7%
b178
9.7%
I12
 
0.7%
Other values (10)38
 
2.1%

notes
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing188
Missing (%)99.5%
Memory size1.6 KiB
2026-01-13T18:40:49.689194image/svg+xmlMatplotlib v3.10.0, 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 (%)
reportedly1
50.0%
blocked1
50.0%
2026-01-13T18:40:49.826532image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e3
16.7%
o2
11.1%
d2
11.1%
l2
11.1%
R1
 
5.6%
r1
 
5.6%
p1
 
5.6%
t1
 
5.6%
y1
 
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 (%)
e3
16.7%
o2
11.1%
d2
11.1%
l2
11.1%
R1
 
5.6%
r1
 
5.6%
p1
 
5.6%
t1
 
5.6%
y1
 
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 (%)
e3
16.7%
o2
11.1%
d2
11.1%
l2
11.1%
R1
 
5.6%
r1
 
5.6%
p1
 
5.6%
t1
 
5.6%
y1
 
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 (%)
e3
16.7%
o2
11.1%
d2
11.1%
l2
11.1%
R1
 
5.6%
r1
 
5.6%
p1
 
5.6%
t1
 
5.6%
y1
 
5.6%
1
 
5.6%
Other values (3)3
16.7%

Correlations

2026-01-13T18:40:49.867144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
category_codesource
category_code1.0000.100
source0.1001.000

Missing values

2026-01-13T18:40:49.209480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2026-01-13T18:40:49.263326image/svg+xmlMatplotlib v3.10.0, 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