# Overview

Brought to you by YData

Dataset statistics

Number of variables | 7
Number of observations | 3398
Missing cells | 11321
Missing cells (%) | 47.6%
Duplicate rows | 0
Duplicate rows (%) | 0.0%
Total size in memory | 186.0 KiB
Average record size in memory | 56.0 B

Variable types

Text | 1
Boolean | 4
Categorical | 2

Alerts

`ability_to_shift_consumption` is highly overall correlated with `have_heard_about_time_of_use_metering` and 1 other fields | High correlation
`have_heard_about_time_of_use_metering` is highly overall correlated with `ability_to_shift_consumption` and 4 other fields | High correlation
`like_to_use_time_of_use_metering` is highly overall correlated with `ability_to_shift_consumption` and 1 other fields | High correlation
`reduced_electricity` is highly overall correlated with `have_heard_about_time_of_use_metering` and 1 other fields | High correlation
`use_of_time_of_use_metering` is highly overall correlated with `have_heard_about_time_of_use_metering` and 2 other fields | High correlation
`why_havent_used_time_of_use_metering` is highly overall correlated with `have_heard_about_time_of_use_metering` and 1 other fields | High correlation
`use_of_time_of_use_metering` has 2303 (67.8%) missing values | Missing
`reduced_electricity` has 2997 (88.2%) missing values | Missing
`why_havent_used_time_of_use_metering` has 2704 (79.6%) missing values | Missing
`like_to_use_time_of_use_metering` has 1095 (32.2%) missing values | Missing
`ability_to_shift_consumption` has 2221 (65.4%) missing values | Missing

Reproduction

Analysis started | 2025-02-27 04:59:35.525224
Analysis finished | 2025-02-27 04:59:36.218282
Duration | 0.69 seconds
Software version | ydata-profiling vv4.11.0
Download configuration | config.json

# Variables

household_ID
Text

Distinct | 3397
Distinct (%) | 100.0%
Missing | 1
Missing (%) | < 0.1%
Memory size | 26.7 KiB

Length

Max length | 6
Median length | 6
Mean length | 6
Min length | 6

Characters and Unicode

Total characters | 20382
Distinct characters | 12
Distinct categories | 1 ?
Distinct scripts | 1 ?
Distinct blocks | 1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique | 3397 ?
Unique (%) | 100.0%

Sample

1st row | ID0726
2nd row | ID0734
3rd row | ID2795
4th row | ID2829
5th row | ID2843

Value | Count | Frequency (%)
id0020 | 1 | < 0.1%
id1050 | 1 | < 0.1%
id0726 | 1 | < 0.1%
id0734 | 1 | < 0.1%
id2795 | 1 | < 0.1%
id3026 | 1 | < 0.1%
id2178 | 1 | < 0.1%
id3804 | 1 | < 0.1%
id0976 | 1 | < 0.1%
id1025 | 1 | < 0.1%
Other values (3387) | 3387 | 99.7%

#### Most occurring characters

Value | Count | Frequency (%)
I | 3397 | 16.7%
D | 3397 | 16.7%
0 | 1913 | 9.4%
3 | 1871 | 9.2%
2 | 1858 | 9.1%
1 | 1837 | 9.0%
4 | 1066 | 5.2%
5 | 1033 | 5.1%
6 | 1028 | 5.0%
9 | 1018 | 5.0%
Other values (2) | 1964 | 9.6%

#### Most occurring categories

Value | Count | Frequency (%)
(unknown) | 20382 | 100.0%

#### Most frequent character per category

##### (unknown)

Value | Count | Frequency (%)
I | 3397 | 16.7%
D | 3397 | 16.7%
0 | 1913 | 9.4%
3 | 1871 | 9.2%
2 | 1858 | 9.1%
1 | 1837 | 9.0%
4 | 1066 | 5.2%
5 | 1033 | 5.1%
6 | 1028 | 5.0%
9 | 1018 | 5.0%
Other values (2) | 1964 | 9.6%

#### Most occurring scripts

Value | Count | Frequency (%)
(unknown) | 20382 | 100.0%

#### Most frequent character per script

##### (unknown)

Value | Count | Frequency (%)
I | 3397 | 16.7%
D | 3397 | 16.7%
0 | 1913 | 9.4%
3 | 1871 | 9.2%
2 | 1858 | 9.1%
1 | 1837 | 9.0%
4 | 1066 | 5.2%
5 | 1033 | 5.1%
6 | 1028 | 5.0%
9 | 1018 | 5.0%
Other values (2) | 1964 | 9.6%

#### Most occurring blocks

Value | Count | Frequency (%)
(unknown) | 20382 | 100.0%

#### Most frequent character per block

##### (unknown)

Value | Count | Frequency (%)
I | 3397 | 16.7%
D | 3397 | 16.7%
0 | 1913 | 9.4%
3 | 1871 | 9.2%
2 | 1858 | 9.1%
1 | 1837 | 9.0%
4 | 1066 | 5.2%
5 | 1033 | 5.1%
6 | 1028 | 5.0%
9 | 1018 | 5.0%
Other values (2) | 1964 | 9.6%

have_heard_about_time_of_use_metering
Boolean

High correlation

Distinct | 2
Distinct (%) | 0.1%
Missing | 0
Missing (%) | 0.0%
Memory size | 3.4 KiB

False | 2303
True | 1095

Value | Count | Frequency (%)
False | 2303 | 67.8%
True | 1095 | 32.2%

use_of_time_of_use_metering
Boolean

High correlation Missing

Distinct | 2
Distinct (%) | 0.2%
Missing | 2303
Missing (%) | 67.8%
Memory size | 6.8 KiB

False | 694
True | 401
(Missing) | 2303

Value | Count | Frequency (%)
False | 694 | 20.4%
True | 401 | 11.8%
(Missing) | 2303 | 67.8%

reduced_electricity
Boolean

High correlation Missing

Distinct | 2
Distinct (%) | 0.5%
Missing | 2997
Missing (%) | 88.2%
Memory size | 6.8 KiB

True | 308
False | 93
(Missing) | 2997

Value | Count | Frequency (%)
True | 308 | 9.1%
False | 93 | 2.7%
(Missing) | 2997 | 88.2%

why_havent_used_time_of_use_metering
Categorical

High correlation Missing

Distinct | 4
Distinct (%) | 0.6%
Missing | 2704
Missing (%) | 79.6%
Memory size | 26.7 KiB

I don’t know how to apply for it | 216
I wanted to apply but couldn’t do it yet | 213
Other (specify) | 155
Don’t think there is any considerable reduction in the electricity bill by using “Time of use monitoring” | 110

Length

Max length | 105
Median length | 40
Mean length | 42.229107
Min length | 15

Characters and Unicode

Total characters | 29307
Distinct characters | 31
Distinct categories | 1 ?
Distinct scripts | 1 ?
Distinct blocks | 1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique | 0 ?
Unique (%) | 0.0%

Sample

1st row | I don’t know how to apply for it
2nd row | I don’t know how to apply for it
3rd row | I wanted to apply but couldn’t do it yet
4th row | I don’t know how to apply for it
5th row | Don’t think there is any considerable reduction in the electricity bill by using “Time of use monitoring”

#### Common Values

Value | Count | Frequency (%)
I don’t know how to apply for it | 216 | 6.4%
I wanted to apply but couldn’t do it yet | 213 | 6.3%
Other (specify) | 155 | 4.6%
Don’t think there is any considerable reduction in the electricity bill by using “Time of use monitoring” | 110 | 3.2%
(Missing) | 2704 | 79.6%

#### Length

Histogram of lengths of the category

#### Common Values (Plot)

Value | Count | Frequency (%)
i | 429 | 7.4%
apply | 429 | 7.4%
to | 429 | 7.4%
it | 429 | 7.4%
don’t | 326 | 5.6%
how | 216 | 3.7%
know | 216 | 3.7%
for | 216 | 3.7%
wanted | 213 | 3.7%
but | 213 | 3.7%
Other values (21) | 2709 | 46.5%

#### Most occurring characters

Value | Count | Frequency (%)
| 5131 | 17.5%
t | 2961 | 10.1%
o | 2379 | 8.1%
i | 1904 | 6.5%
n | 1848 | 6.3%
e | 1836 | 6.3%
y | 1127 | 3.8%
l | 1082 | 3.7%
d | 1075 | 3.7%
p | 1013 | 3.5%
Other values (21) | 8951 | 30.5%

#### Most occurring categories

Value | Count | Frequency (%)
(unknown) | 29307 | 100.0%

#### Most frequent character per category

##### (unknown)

Value | Count | Frequency (%)
| 5131 | 17.5%
t | 2961 | 10.1%
o | 2379 | 8.1%
i | 1904 | 6.5%
n | 1848 | 6.3%
e | 1836 | 6.3%
y | 1127 | 3.8%
l | 1082 | 3.7%
d | 1075 | 3.7%
p | 1013 | 3.5%
Other values (21) | 8951 | 30.5%

#### Most occurring scripts

Value | Count | Frequency (%)
(unknown) | 29307 | 100.0%

#### Most frequent character per script

##### (unknown)

Value | Count | Frequency (%)
| 5131 | 17.5%
t | 2961 | 10.1%
o | 2379 | 8.1%
i | 1904 | 6.5%
n | 1848 | 6.3%
e | 1836 | 6.3%
y | 1127 | 3.8%
l | 1082 | 3.7%
d | 1075 | 3.7%
p | 1013 | 3.5%
Other values (21) | 8951 | 30.5%

#### Most occurring blocks

Value | Count | Frequency (%)
(unknown) | 29307 | 100.0%

#### Most frequent character per block

##### (unknown)

Value | Count | Frequency (%)
| 5131 | 17.5%
t | 2961 | 10.1%
o | 2379 | 8.1%
i | 1904 | 6.5%
n | 1848 | 6.3%
e | 1836 | 6.3%
y | 1127 | 3.8%
l | 1082 | 3.7%
d | 1075 | 3.7%
p | 1013 | 3.5%
Other values (21) | 8951 | 30.5%

like_to_use_time_of_use_metering
Categorical

High correlation Missing

Distinct | 3
Distinct (%) | 0.1%
Missing | 1095
Missing (%) | 32.2%
Memory size | 26.7 KiB

Yes | 1177
No | 837
Can't Say | 289

Length

Max length | 9
Median length | 3
Mean length | 3.389492
Min length | 2

Characters and Unicode

Total characters | 7806
Distinct characters | 13
Distinct categories | 1 ?
Distinct scripts | 1 ?
Distinct blocks | 1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique | 0 ?
Unique (%) | 0.0%

Sample

1st row | Yes
2nd row | Yes
3rd row | Yes
4th row | Yes
5th row | Yes

#### Common Values

Value | Count | Frequency (%)
Yes | 1177 | 34.6%
No | 837 | 24.6%
Can't Say | 289 | 8.5%
(Missing) | 1095 | 32.2%

#### Length

Histogram of lengths of the category

#### Common Values (Plot)

Value | Count | Frequency (%)
yes | 1177 | 45.4%
no | 837 | 32.3%
can't | 289 | 11.1%
say | 289 | 11.1%

#### Most occurring characters

Value | Count | Frequency (%)
Y | 1177 | 15.1%
e | 1177 | 15.1%
s | 1177 | 15.1%
N | 837 | 10.7%
o | 837 | 10.7%
a | 578 | 7.4%
C | 289 | 3.7%
n | 289 | 3.7%
' | 289 | 3.7%
t | 289 | 3.7%
Other values (3) | 867 | 11.1%

#### Most occurring categories

Value | Count | Frequency (%)
(unknown) | 7806 | 100.0%

#### Most frequent character per category

##### (unknown)

Value | Count | Frequency (%)
Y | 1177 | 15.1%
e | 1177 | 15.1%
s | 1177 | 15.1%
N | 837 | 10.7%
o | 837 | 10.7%
a | 578 | 7.4%
C | 289 | 3.7%
n | 289 | 3.7%
' | 289 | 3.7%
t | 289 | 3.7%
Other values (3) | 867 | 11.1%

#### Most occurring scripts

Value | Count | Frequency (%)
(unknown) | 7806 | 100.0%

#### Most frequent character per script

##### (unknown)

Value | Count | Frequency (%)
Y | 1177 | 15.1%
e | 1177 | 15.1%
s | 1177 | 15.1%
N | 837 | 10.7%
o | 837 | 10.7%
a | 578 | 7.4%
C | 289 | 3.7%
n | 289 | 3.7%
' | 289 | 3.7%
t | 289 | 3.7%
Other values (3) | 867 | 11.1%

#### Most occurring blocks

Value | Count | Frequency (%)
(unknown) | 7806 | 100.0%

#### Most frequent character per block

##### (unknown)

Value | Count | Frequency (%)
Y | 1177 | 15.1%
e | 1177 | 15.1%
s | 1177 | 15.1%
N | 837 | 10.7%
o | 837 | 10.7%
a | 578 | 7.4%
C | 289 | 3.7%
n | 289 | 3.7%
' | 289 | 3.7%
t | 289 | 3.7%
Other values (3) | 867 | 11.1%

ability_to_shift_consumption
Boolean

High correlation Missing

Distinct | 2
Distinct (%) | 0.2%
Missing | 2221
Missing (%) | 65.4%
Memory size | 6.8 KiB

True | 1025
False | 152
(Missing) | 2221

Value | Count | Frequency (%)
True | 1025 | 30.2%
False | 152 | 4.5%
(Missing) | 2221 | 65.4%

# Correlations

| ability_to_shift_consumption | have_heard_about_time_of_use_metering | like_to_use_time_of_use_metering | reduced_electricity | use_of_time_of_use_metering | why_havent_used_time_of_use_metering
--- | --- | --- | --- | --- | --- | ---
ability_to_shift_consumption | 1.000 | 1.000 | 1.000 | 0.000 | 0.000 | 0.000
have_heard_about_time_of_use_metering | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000
like_to_use_time_of_use_metering | 1.000 | 1.000 | 1.000 | 0.000 | 0.000 | 0.000
reduced_electricity | 0.000 | 1.000 | 0.000 | 1.000 | 1.000 | 0.000
use_of_time_of_use_metering | 0.000 | 1.000 | 0.000 | 1.000 | 1.000 | 1.000
why_havent_used_time_of_use_metering | 0.000 | 1.000 | 0.000 | 0.000 | 1.000 | 1.000

# Missing values

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 correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

# Sample

| household_ID | have_heard_about_time_of_use_metering | use_of_time_of_use_metering | reduced_electricity | why_havent_used_time_of_use_metering | like_to_use_time_of_use_metering | ability_to_shift_consumption
--- | --- | --- | --- | --- | --- | --- | ---
0 | ID0726 | No | NaN | NaN | NaN | Yes | Yes
1 | ID0734 | No | NaN | NaN | NaN | Yes | Yes
2 | ID2795 | Yes | Yes | Yes | NaN | NaN | NaN
3 | ID2829 | No | NaN | NaN | NaN | Yes | Yes
4 | ID2843 | Yes | Yes | Yes | NaN | NaN | NaN
5 | ID2906 | No | NaN | NaN | NaN | Yes | Yes
6 | ID2908 | No | NaN | NaN | NaN | Yes | Yes
7 | ID2917 | No | NaN | NaN | NaN | Yes | Yes
8 | ID2836 | No | NaN | NaN | NaN | No | NaN
9 | ID2915 | No | NaN | NaN | NaN | No | NaN

| household_ID | have_heard_about_time_of_use_metering | use_of_time_of_use_metering | reduced_electricity | why_havent_used_time_of_use_metering | like_to_use_time_of_use_metering | ability_to_shift_consumption
--- | --- | --- | --- | --- | --- | --- | ---
3388 | ID3458 | No | NaN | NaN | NaN | Yes | No
3389 | ID3064 | No | NaN | NaN | NaN | Yes | Yes
3390 | ID0586 | No | NaN | NaN | NaN | Can't Say | NaN
3391 | ID0403 | No | NaN | NaN | NaN | No | NaN
3392 | ID2268 | Yes | Yes | No | NaN | NaN | NaN
3393 | ID1147 | No | NaN | NaN | NaN | No | NaN
3394 | ID0963 | No | NaN | NaN | NaN | Yes | No
3395 | ID1024 | Yes | No | NaN | I don’t know how to apply for it | NaN | NaN
3396 | ID2440 | Yes | Yes | Yes | NaN | NaN | NaN
3397 | ID1050 | No | NaN | NaN | NaN | No | NaN