# Overview

Brought to you by YData

Dataset statistics

Number of variables | 17
Number of observations | 3398
Missing cells | 46058
Missing cells (%) | 79.7%
Duplicate rows | 0
Duplicate rows (%) | 0.0%
Total size in memory | 451.4 KiB
Average record size in memory | 136.0 B

Variable types

Text | 1
Categorical | 11
Unsupported | 3
Numeric | 2

Alerts

`solar_energy_used_for_outdoor_lighting` has constant value "3.0" | Constant
`aware_of_no_of_units_generated_by_solar_system` is highly overall correlated with `installed_a_solar_system_after_w1` and 4 other fields | High correlation
`capacity_of_the_solar_system` is highly overall correlated with `installed_a_solar_system_after_w1` and 2 other fields | High correlation
`had_solar_energy_when_w2_was_done` is highly overall correlated with `increased_or_decreased_no_of_panels_after_w1` and 4 other fields | High correlation
`increased_or_decreased_no_of_panels_after_w1` is highly overall correlated with `had_solar_energy_when_w2_was_done` and 3 other fields | High correlation
`installed_a_solar_system_after_w1` is highly overall correlated with `aware_of_no_of_units_generated_by_solar_system` and 6 other fields | High correlation
`no_of_units_generated_last_month` is highly overall correlated with `aware_of_no_of_units_generated_by_solar_system` and 5 other fields | High correlation
`solar_energy_used_for_car_charging` is highly overall correlated with `aware_of_no_of_units_generated_by_solar_system` and 9 other fields | High correlation
`solar_energy_used_for_cooking` is highly overall correlated with `aware_of_no_of_units_generated_by_solar_system` and 8 other fields | High correlation
`solar_energy_used_for_water_heating` is highly overall correlated with `installed_a_solar_system_after_w1` and 5 other fields | High correlation
`solar_system_inverter_or_non_inverter` is highly overall correlated with `installed_a_solar_system_after_w1` and 3 other fields | High correlation
`solar_system_ongrid_or_offgrid` is highly overall correlated with `installed_a_solar_system_after_w1` and 4 other fields | High correlation
`still_have_the_solar_system_from_w1` is highly overall correlated with `aware_of_no_of_units_generated_by_solar_system` and 9 other fields | High correlation
`had_solar_energy_when_w2_was_done` is highly imbalanced (60.9%) | Imbalance
`installed_a_solar_system_after_w1` is highly imbalanced (92.0%) | Imbalance
`still_have_the_solar_system_from_w1` is highly imbalanced (74.8%) | Imbalance
`increased_or_decreased_no_of_panels_after_w1` is highly imbalanced (81.2%) | Imbalance
`solar_system_ongrid_or_offgrid` is highly imbalanced (51.9%) | Imbalance
`installed_a_solar_system_after_w1` has 261 (7.7%) missing values | Missing
`still_have_the_solar_system_from_w1` has 3137 (92.3%) missing values | Missing
`increased_or_decreased_no_of_panels_after_w1` has 3148 (92.6%) missing values | Missing
`solar_system_ongrid_or_offgrid` has 3117 (91.7%) missing values | Missing
`solar_system_inverter_or_non_inverter` has 3117 (91.7%) missing values | Missing
`solar_energy_used_for_water_heating` has 3364 (99.0%) missing values | Missing
`solar_energy_used_for_cooking` has 3394 (99.9%) missing values | Missing
`solar_energy_used_for_outdoor_lighting` has 3396 (99.9%) missing values | Missing
`solar_energy_used_for_car_charging` has 3396 (99.9%) missing values | Missing
`solar_energy_used_for_agricultural_systems` has 3398 (100.0%) missing values | Missing
`solar_energy_used_for_all_above` has 3398 (100.0%) missing values | Missing
`solar_energy_used_for_other_purposes` has 3398 (100.0%) missing values | Missing
`aware_of_no_of_units_generated_by_solar_system` has 3117 (91.7%) missing values | Missing
`no_of_units_generated_last_month` has 3299 (97.1%) missing values | Missing
`capacity_of_the_solar_system` has 3117 (91.7%) missing values | Missing
`solar_energy_used_for_car_charging` is uniformly distributed | Uniform
`solar_energy_used_for_agricultural_systems` is an unsupported type, check if it needs cleaning or further analysis | Unsupported
`solar_energy_used_for_all_above` is an unsupported type, check if it needs cleaning or further analysis | Unsupported
`solar_energy_used_for_other_purposes` is an unsupported type, check if it needs cleaning or further analysis | Unsupported
`capacity_of_the_solar_system` has 140 (4.1%) zeros | Zeros

Reproduction

Analysis started | 2025-02-27 04:59:46.051993
Analysis finished | 2025-02-27 04:59:47.426813
Duration | 1.37 second
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%

had_solar_energy_when_w2_was_done
Categorical

High correlation Imbalance

Distinct | 2
Distinct (%) | 0.1%
Missing | 0
Missing (%) | 0.0%
Memory size | 26.7 KiB

2.0 | 3137
1.0 | 261

Length

Max length | 3
Median length | 3
Mean length | 3
Min length | 3

Characters and Unicode

Total characters | 10194
Distinct characters | 4
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 | 2.0
2nd row | 2.0
3rd row | 2.0
4th row | 2.0
5th row | 2.0

#### Common Values

Value | Count | Frequency (%)
2.0 | 3137 | 92.3%
1.0 | 261 | 7.7%

#### Length

Histogram of lengths of the category

#### Common Values (Plot)

Value | Count | Frequency (%)
2.0 | 3137 | 92.3%
1.0 | 261 | 7.7%

#### Most occurring characters

Value | Count | Frequency (%)
. | 3398 | 33.3%
0 | 3398 | 33.3%
2 | 3137 | 30.8%
1 | 261 | 2.6%

#### Most occurring categories

Value | Count | Frequency (%)
(unknown) | 10194 | 100.0%

#### Most frequent character per category

##### (unknown)

Value | Count | Frequency (%)
. | 3398 | 33.3%
0 | 3398 | 33.3%
2 | 3137 | 30.8%
1 | 261 | 2.6%

#### Most occurring scripts

Value | Count | Frequency (%)
(unknown) | 10194 | 100.0%

#### Most frequent character per script

##### (unknown)

Value | Count | Frequency (%)
. | 3398 | 33.3%
0 | 3398 | 33.3%
2 | 3137 | 30.8%
1 | 261 | 2.6%

#### Most occurring blocks

Value | Count | Frequency (%)
(unknown) | 10194 | 100.0%

#### Most frequent character per block

##### (unknown)

Value | Count | Frequency (%)
. | 3398 | 33.3%
0 | 3398 | 33.3%
2 | 3137 | 30.8%
1 | 261 | 2.6%

installed_a_solar_system_after_w1
Categorical

High correlation Imbalance Missing

Distinct | 2
Distinct (%) | 0.1%
Missing | 261
Missing (%) | 7.7%
Memory size | 26.7 KiB

2.0 | 3106
1.0 | 31

Length

Max length | 3
Median length | 3
Mean length | 3
Min length | 3

Characters and Unicode

Total characters | 9411
Distinct characters | 4
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 | 2.0
2nd row | 2.0
3rd row | 2.0
4th row | 2.0
5th row | 2.0

#### Common Values

Value | Count | Frequency (%)
2.0 | 3106 | 91.4%
1.0 | 31 | 0.9%
(Missing) | 261 | 7.7%

#### Length

Histogram of lengths of the category

#### Common Values (Plot)

Value | Count | Frequency (%)
2.0 | 3106 | 99.0%
1.0 | 31 | 1.0%

#### Most occurring characters

Value | Count | Frequency (%)
. | 3137 | 33.3%
0 | 3137 | 33.3%
2 | 3106 | 33.0%
1 | 31 | 0.3%

#### Most occurring categories

Value | Count | Frequency (%)
(unknown) | 9411 | 100.0%

#### Most frequent character per category

##### (unknown)

Value | Count | Frequency (%)
. | 3137 | 33.3%
0 | 3137 | 33.3%
2 | 3106 | 33.0%
1 | 31 | 0.3%

#### Most occurring scripts

Value | Count | Frequency (%)
(unknown) | 9411 | 100.0%

#### Most frequent character per script

##### (unknown)

Value | Count | Frequency (%)
. | 3137 | 33.3%
0 | 3137 | 33.3%
2 | 3106 | 33.0%
1 | 31 | 0.3%

#### Most occurring blocks

Value | Count | Frequency (%)
(unknown) | 9411 | 100.0%

#### Most frequent character per block

##### (unknown)

Value | Count | Frequency (%)
. | 3137 | 33.3%
0 | 3137 | 33.3%
2 | 3106 | 33.0%
1 | 31 | 0.3%

still_have_the_solar_system_from_w1
Categorical

High correlation Imbalance Missing

Distinct | 2
Distinct (%) | 0.8%
Missing | 3137
Missing (%) | 92.3%
Memory size | 26.7 KiB

1.0 | 250
2.0 | 11

Length

Max length | 3
Median length | 3
Mean length | 3
Min length | 3

Characters and Unicode

Total characters | 783
Distinct characters | 4
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 | 1.0
2nd row | 1.0
3rd row | 1.0
4th row | 1.0
5th row | 1.0

#### Common Values

Value | Count | Frequency (%)
1.0 | 250 | 7.4%
2.0 | 11 | 0.3%
(Missing) | 3137 | 92.3%

#### Length

Histogram of lengths of the category

#### Common Values (Plot)

Value | Count | Frequency (%)
1.0 | 250 | 95.8%
2.0 | 11 | 4.2%

#### Most occurring characters

Value | Count | Frequency (%)
. | 261 | 33.3%
0 | 261 | 33.3%
1 | 250 | 31.9%
2 | 11 | 1.4%

#### Most occurring categories

Value | Count | Frequency (%)
(unknown) | 783 | 100.0%

#### Most frequent character per category

##### (unknown)

Value | Count | Frequency (%)
. | 261 | 33.3%
0 | 261 | 33.3%
1 | 250 | 31.9%
2 | 11 | 1.4%

#### Most occurring scripts

Value | Count | Frequency (%)
(unknown) | 783 | 100.0%

#### Most frequent character per script

##### (unknown)

Value | Count | Frequency (%)
. | 261 | 33.3%
0 | 261 | 33.3%
1 | 250 | 31.9%
2 | 11 | 1.4%

#### Most occurring blocks

Value | Count | Frequency (%)
(unknown) | 783 | 100.0%

#### Most frequent character per block

##### (unknown)

Value | Count | Frequency (%)
. | 261 | 33.3%
0 | 261 | 33.3%
1 | 250 | 31.9%
2 | 11 | 1.4%

increased_or_decreased_no_of_panels_after_w1
Categorical

High correlation Imbalance Missing

Distinct | 3
Distinct (%) | 1.2%
Missing | 3148
Missing (%) | 92.6%
Memory size | 26.7 KiB

3.0 | 239
1.0 | 8
2.0 | 3

Length

Max length | 3
Median length | 3
Mean length | 3
Min length | 3

Characters and Unicode

Total characters | 750
Distinct characters | 5
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 | 3.0
2nd row | 3.0
3rd row | 3.0
4th row | 3.0
5th row | 3.0

#### Common Values

Value | Count | Frequency (%)
3.0 | 239 | 7.0%
1.0 | 8 | 0.2%
2.0 | 3 | 0.1%
(Missing) | 3148 | 92.6%

#### Length

Histogram of lengths of the category

#### Common Values (Plot)

Value | Count | Frequency (%)
3.0 | 239 | 95.6%
1.0 | 8 | 3.2%
2.0 | 3 | 1.2%

#### Most occurring characters

Value | Count | Frequency (%)
. | 250 | 33.3%
0 | 250 | 33.3%
3 | 239 | 31.9%
1 | 8 | 1.1%
2 | 3 | 0.4%

#### Most occurring categories

Value | Count | Frequency (%)
(unknown) | 750 | 100.0%

#### Most frequent character per category

##### (unknown)

Value | Count | Frequency (%)
. | 250 | 33.3%
0 | 250 | 33.3%
3 | 239 | 31.9%
1 | 8 | 1.1%
2 | 3 | 0.4%

#### Most occurring scripts

Value | Count | Frequency (%)
(unknown) | 750 | 100.0%

#### Most frequent character per script

##### (unknown)

Value | Count | Frequency (%)
. | 250 | 33.3%
0 | 250 | 33.3%
3 | 239 | 31.9%
1 | 8 | 1.1%
2 | 3 | 0.4%

#### Most occurring blocks

Value | Count | Frequency (%)
(unknown) | 750 | 100.0%

#### Most frequent character per block

##### (unknown)

Value | Count | Frequency (%)
. | 250 | 33.3%
0 | 250 | 33.3%
3 | 239 | 31.9%
1 | 8 | 1.1%
2 | 3 | 0.4%

solar_system_ongrid_or_offgrid
Categorical

High correlation Imbalance Missing

Distinct | 3
Distinct (%) | 1.1%
Missing | 3117
Missing (%) | 91.7%
Memory size | 26.7 KiB

1.0 | 236
2.0 | 34
9.0 | 11

Length

Max length | 3
Median length | 3
Mean length | 3
Min length | 3

Characters and Unicode

Total characters | 843
Distinct characters | 5
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 | 1.0
2nd row | 1.0
3rd row | 1.0
4th row | 1.0
5th row | 2.0

#### Common Values

Value | Count | Frequency (%)
1.0 | 236 | 6.9%
2.0 | 34 | 1.0%
9.0 | 11 | 0.3%
(Missing) | 3117 | 91.7%

#### Length

Histogram of lengths of the category

#### Common Values (Plot)

Value | Count | Frequency (%)
1.0 | 236 | 84.0%
2.0 | 34 | 12.1%
9.0 | 11 | 3.9%

#### Most occurring characters

Value | Count | Frequency (%)
. | 281 | 33.3%
0 | 281 | 33.3%
1 | 236 | 28.0%
2 | 34 | 4.0%
9 | 11 | 1.3%

#### Most occurring categories

Value | Count | Frequency (%)
(unknown) | 843 | 100.0%

#### Most frequent character per category

##### (unknown)

Value | Count | Frequency (%)
. | 281 | 33.3%
0 | 281 | 33.3%
1 | 236 | 28.0%
2 | 34 | 4.0%
9 | 11 | 1.3%

#### Most occurring scripts

Value | Count | Frequency (%)
(unknown) | 843 | 100.0%

#### Most frequent character per script

##### (unknown)

Value | Count | Frequency (%)
. | 281 | 33.3%
0 | 281 | 33.3%
1 | 236 | 28.0%
2 | 34 | 4.0%
9 | 11 | 1.3%

#### Most occurring blocks

Value | Count | Frequency (%)
(unknown) | 843 | 100.0%

#### Most frequent character per block

##### (unknown)

Value | Count | Frequency (%)
. | 281 | 33.3%
0 | 281 | 33.3%
1 | 236 | 28.0%
2 | 34 | 4.0%
9 | 11 | 1.3%

solar_system_inverter_or_non_inverter
Categorical

High correlation Missing

Distinct | 2
Distinct (%) | 0.7%
Missing | 3117
Missing (%) | 91.7%
Memory size | 26.7 KiB

1.0 | 202
0.0 | 79

Length

Max length | 3
Median length | 3
Mean length | 3
Min length | 3

Characters and Unicode

Total characters | 843
Distinct characters | 3
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 | 1.0
2nd row | 1.0
3rd row | 0.0
4th row | 1.0
5th row | 1.0

#### Common Values

Value | Count | Frequency (%)
1.0 | 202 | 5.9%
0.0 | 79 | 2.3%
(Missing) | 3117 | 91.7%

#### Length

Histogram of lengths of the category

#### Common Values (Plot)

Value | Count | Frequency (%)
1.0 | 202 | 71.9%
0.0 | 79 | 28.1%

#### Most occurring characters

Value | Count | Frequency (%)
0 | 360 | 42.7%
. | 281 | 33.3%
1 | 202 | 24.0%

#### Most occurring categories

Value | Count | Frequency (%)
(unknown) | 843 | 100.0%

#### Most frequent character per category

##### (unknown)

Value | Count | Frequency (%)
0 | 360 | 42.7%
. | 281 | 33.3%
1 | 202 | 24.0%

#### Most occurring scripts

Value | Count | Frequency (%)
(unknown) | 843 | 100.0%

#### Most frequent character per script

##### (unknown)

Value | Count | Frequency (%)
0 | 360 | 42.7%
. | 281 | 33.3%
1 | 202 | 24.0%

#### Most occurring blocks

Value | Count | Frequency (%)
(unknown) | 843 | 100.0%

#### Most frequent character per block

##### (unknown)

Value | Count | Frequency (%)
0 | 360 | 42.7%
. | 281 | 33.3%
1 | 202 | 24.0%

solar_energy_used_for_water_heating
Categorical

High correlation Missing

Distinct | 4
Distinct (%) | 11.8%
Missing | 3364
Missing (%) | 99.0%
Memory size | 26.7 KiB

3.0 | 14
1.0 | 13
6.0 | 5
7.0 | 2

Length

Max length | 3
Median length | 3
Mean length | 3
Min length | 3

Characters and Unicode

Total characters | 102
Distinct characters | 6
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 | 1.0
2nd row | 3.0
3rd row | 3.0
4th row | 3.0
5th row | 3.0

#### Common Values

Value | Count | Frequency (%)
3.0 | 14 | 0.4%
1.0 | 13 | 0.4%
6.0 | 5 | 0.1%
7.0 | 2 | 0.1%
(Missing) | 3364 | 99.0%

#### Length

Histogram of lengths of the category

#### Common Values (Plot)

Value | Count | Frequency (%)
3.0 | 14 | 41.2%
1.0 | 13 | 38.2%
6.0 | 5 | 14.7%
7.0 | 2 | 5.9%

#### Most occurring characters

Value | Count | Frequency (%)
. | 34 | 33.3%
0 | 34 | 33.3%
3 | 14 | 13.7%
1 | 13 | 12.7%
6 | 5 | 4.9%
7 | 2 | 2.0%

#### Most occurring categories

Value | Count | Frequency (%)
(unknown) | 102 | 100.0%

#### Most frequent character per category

##### (unknown)

Value | Count | Frequency (%)
. | 34 | 33.3%
0 | 34 | 33.3%
3 | 14 | 13.7%
1 | 13 | 12.7%
6 | 5 | 4.9%
7 | 2 | 2.0%

#### Most occurring scripts

Value | Count | Frequency (%)
(unknown) | 102 | 100.0%

#### Most frequent character per script

##### (unknown)

Value | Count | Frequency (%)
. | 34 | 33.3%
0 | 34 | 33.3%
3 | 14 | 13.7%
1 | 13 | 12.7%
6 | 5 | 4.9%
7 | 2 | 2.0%

#### Most occurring blocks

Value | Count | Frequency (%)
(unknown) | 102 | 100.0%

#### Most frequent character per block

##### (unknown)

Value | Count | Frequency (%)
. | 34 | 33.3%
0 | 34 | 33.3%
3 | 14 | 13.7%
1 | 13 | 12.7%
6 | 5 | 4.9%
7 | 2 | 2.0%

solar_energy_used_for_cooking
Categorical

High correlation Missing

Distinct | 3
Distinct (%) | 75.0%
Missing | 3394
Missing (%) | 99.9%
Memory size | 26.7 KiB

2.0 | 2
7.0 | 1
3.0 | 1

Length

Max length | 3
Median length | 3
Mean length | 3
Min length | 3

Characters and Unicode

Total characters | 12
Distinct characters | 5
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 | 2 ?
Unique (%) | 50.0%

Sample

1st row | 7.0
2nd row | 2.0
3rd row | 2.0
4th row | 3.0

#### Common Values

Value | Count | Frequency (%)
2.0 | 2 | 0.1%
7.0 | 1 | < 0.1%
3.0 | 1 | < 0.1%
(Missing) | 3394 | 99.9%

#### Length

Histogram of lengths of the category

#### Common Values (Plot)

Value | Count | Frequency (%)
2.0 | 2 | 50.0%
7.0 | 1 | 25.0%
3.0 | 1 | 25.0%

#### Most occurring characters

Value | Count | Frequency (%)
. | 4 | 33.3%
0 | 4 | 33.3%
2 | 2 | 16.7%
7 | 1 | 8.3%
3 | 1 | 8.3%

#### Most occurring categories

Value | Count | Frequency (%)
(unknown) | 12 | 100.0%

#### Most frequent character per category

##### (unknown)

Value | Count | Frequency (%)
. | 4 | 33.3%
0 | 4 | 33.3%
2 | 2 | 16.7%
7 | 1 | 8.3%
3 | 1 | 8.3%

#### Most occurring scripts

Value | Count | Frequency (%)
(unknown) | 12 | 100.0%

#### Most frequent character per script

##### (unknown)

Value | Count | Frequency (%)
. | 4 | 33.3%
0 | 4 | 33.3%
2 | 2 | 16.7%
7 | 1 | 8.3%
3 | 1 | 8.3%

#### Most occurring blocks

Value | Count | Frequency (%)
(unknown) | 12 | 100.0%

#### Most frequent character per block

##### (unknown)

Value | Count | Frequency (%)
. | 4 | 33.3%
0 | 4 | 33.3%
2 | 2 | 16.7%
7 | 1 | 8.3%
3 | 1 | 8.3%

solar_energy_used_for_outdoor_lighting
Categorical

Constant Missing

Distinct | 1
Distinct (%) | 50.0%
Missing | 3396
Missing (%) | 99.9%
Memory size | 26.7 KiB

3.0 | 2

Length

Max length | 3
Median length | 3
Mean length | 3
Min length | 3

Characters and Unicode

Total characters | 6
Distinct characters | 3
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 | 3.0
2nd row | 3.0

#### Common Values

Value | Count | Frequency (%)
3.0 | 2 | 0.1%
(Missing) | 3396 | 99.9%

#### Length

Histogram of lengths of the category

#### Common Values (Plot)

Value | Count | Frequency (%)
3.0 | 2 | 100.0%

#### Most occurring characters

Value | Count | Frequency (%)
3 | 2 | 33.3%
. | 2 | 33.3%
0 | 2 | 33.3%

#### Most occurring categories

Value | Count | Frequency (%)
(unknown) | 6 | 100.0%

#### Most frequent character per category

##### (unknown)

Value | Count | Frequency (%)
3 | 2 | 33.3%
. | 2 | 33.3%
0 | 2 | 33.3%

#### Most occurring scripts

Value | Count | Frequency (%)
(unknown) | 6 | 100.0%

#### Most frequent character per script

##### (unknown)

Value | Count | Frequency (%)
3 | 2 | 33.3%
. | 2 | 33.3%
0 | 2 | 33.3%

#### Most occurring blocks

Value | Count | Frequency (%)
(unknown) | 6 | 100.0%

#### Most frequent character per block

##### (unknown)

Value | Count | Frequency (%)
3 | 2 | 33.3%
. | 2 | 33.3%
0 | 2 | 33.3%

solar_energy_used_for_car_charging
Categorical

High correlation Missing Uniform

Distinct | 2
Distinct (%) | 100.0%
Missing | 3396
Missing (%) | 99.9%
Memory size | 26.7 KiB

5.0 | 1
7.0 | 1

Length

Max length | 3
Median length | 3
Mean length | 3
Min length | 3

Characters and Unicode

Total characters | 6
Distinct characters | 4
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 | 2 ?
Unique (%) | 100.0%

Sample

1st row | 5.0
2nd row | 7.0

#### Common Values

Value | Count | Frequency (%)
5.0 | 1 | < 0.1%
7.0 | 1 | < 0.1%
(Missing) | 3396 | 99.9%

#### Length

Histogram of lengths of the category

#### Common Values (Plot)

Value | Count | Frequency (%)
5.0 | 1 | 50.0%
7.0 | 1 | 50.0%

#### Most occurring characters

Value | Count | Frequency (%)
. | 2 | 33.3%
0 | 2 | 33.3%
5 | 1 | 16.7%
7 | 1 | 16.7%

#### Most occurring categories

Value | Count | Frequency (%)
(unknown) | 6 | 100.0%

#### Most frequent character per category

##### (unknown)

Value | Count | Frequency (%)
. | 2 | 33.3%
0 | 2 | 33.3%
5 | 1 | 16.7%
7 | 1 | 16.7%

#### Most occurring scripts

Value | Count | Frequency (%)
(unknown) | 6 | 100.0%

#### Most frequent character per script

##### (unknown)

Value | Count | Frequency (%)
. | 2 | 33.3%
0 | 2 | 33.3%
5 | 1 | 16.7%
7 | 1 | 16.7%

#### Most occurring blocks

Value | Count | Frequency (%)
(unknown) | 6 | 100.0%

#### Most frequent character per block

##### (unknown)

Value | Count | Frequency (%)
. | 2 | 33.3%
0 | 2 | 33.3%
5 | 1 | 16.7%
7 | 1 | 16.7%

solar_energy_used_for_agricultural_systems
Unsupported

Missing Rejected Unsupported

Missing | 3398
Missing (%) | 100.0%
Memory size | 26.7 KiB

solar_energy_used_for_all_above
Unsupported

Missing Rejected Unsupported

Missing | 3398
Missing (%) | 100.0%
Memory size | 26.7 KiB

solar_energy_used_for_other_purposes
Unsupported

Missing Rejected Unsupported

Missing | 3398
Missing (%) | 100.0%
Memory size | 26.7 KiB

aware_of_no_of_units_generated_by_solar_system
Categorical

High correlation Missing

Distinct | 2
Distinct (%) | 0.7%
Missing | 3117
Missing (%) | 91.7%
Memory size | 26.7 KiB

0.0 | 182
1.0 | 99

Length

Max length | 3
Median length | 3
Mean length | 3
Min length | 3

Characters and Unicode

Total characters | 843
Distinct characters | 3
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 | 0.0
2nd row | 0.0
3rd row | 1.0
4th row | 1.0
5th row | 0.0

#### Common Values

Value | Count | Frequency (%)
0.0 | 182 | 5.4%
1.0 | 99 | 2.9%
(Missing) | 3117 | 91.7%

#### Length

Histogram of lengths of the category

#### Common Values (Plot)

Value | Count | Frequency (%)
0.0 | 182 | 64.8%
1.0 | 99 | 35.2%

#### Most occurring characters

Value | Count | Frequency (%)
0 | 463 | 54.9%
. | 281 | 33.3%
1 | 99 | 11.7%

#### Most occurring categories

Value | Count | Frequency (%)
(unknown) | 843 | 100.0%

#### Most frequent character per category

##### (unknown)

Value | Count | Frequency (%)
0 | 463 | 54.9%
. | 281 | 33.3%
1 | 99 | 11.7%

#### Most occurring scripts

Value | Count | Frequency (%)
(unknown) | 843 | 100.0%

#### Most frequent character per script

##### (unknown)

Value | Count | Frequency (%)
0 | 463 | 54.9%
. | 281 | 33.3%
1 | 99 | 11.7%

#### Most occurring blocks

Value | Count | Frequency (%)
(unknown) | 843 | 100.0%

#### Most frequent character per block

##### (unknown)

Value | Count | Frequency (%)
0 | 463 | 54.9%
. | 281 | 33.3%
1 | 99 | 11.7%

no_of_units_generated_last_month
Real number (ℝ)

High correlation Missing

Distinct | 62
Distinct (%) | 62.6%
Missing | 3299
Missing (%) | 97.1%
Infinite | 0
Infinite (%) | 0.0%
Mean | 449.62626

Minimum | 0
Maximum | 2500
Zeros | 11
Zeros (%) | 0.3%
Negative | 0
Negative (%) | 0.0%
Memory size | 26.7 KiB

Quantile statistics

Minimum | 0
5-th percentile | 0
Q1 | 211
median | 400
Q3 | 595
95-th percentile | 930
Maximum | 2500
Range | 2500
Interquartile range (IQR) | 384

Descriptive statistics

Standard deviation | 408.64179
Coefficient of variation (CV) | 0.90884769
Kurtosis | 8.877932
Mean | 449.62626
Median Absolute Deviation (MAD) | 200
Skewness | 2.447919
Sum | 44513
Variance | 166988.11
Monotonicity | Not monotonic

Histogram with fixed size bins (bins=50)

Value | Count | Frequency (%)
0 | 11 | 0.3%
400 | 5 | 0.1%
450 | 5 | 0.1%
600 | 5 | 0.1%
500 | 4 | 0.1%
650 | 3 | 0.1%
415 | 2 | 0.1%
375 | 2 | 0.1%
350 | 2 | 0.1%
120 | 2 | 0.1%
Other values (52) | 58 | 1.7%
(Missing) | 3299 | 97.1%

Value | Count | Frequency (%)
0 | 11 | 0.3%
5 | 2 | 0.1%
8 | 1 | < 0.1%
35 | 1 | < 0.1%
43 | 1 | < 0.1%
120 | 2 | 0.1%
155 | 1 | < 0.1%
160 | 1 | < 0.1%
168 | 1 | < 0.1%
180 | 1 | < 0.1%

Value | Count | Frequency (%)
2500 | 1 | < 0.1%
2000 | 1 | < 0.1%
1900 | 1 | < 0.1%
1600 | 1 | < 0.1%
1200 | 1 | < 0.1%
900 | 1 | < 0.1%
816 | 1 | < 0.1%
800 | 2 | 0.1%
750 | 1 | < 0.1%
702 | 1 | < 0.1%

capacity_of_the_solar_system
Real number (ℝ)

High correlation Missing Zeros

Distinct | 46
Distinct (%) | 16.4%
Missing | 3117
Missing (%) | 91.7%
Infinite | 0
Infinite (%) | 0.0%
Mean | 769.4911

Minimum | 0
Maximum | 9999
Zeros | 140
Zeros (%) | 4.1%
Negative | 0
Negative (%) | 0.0%
Memory size | 26.7 KiB

Quantile statistics

Minimum | 0
5-th percentile | 0
Q1 | 0
median | 1
Q3 | 7
95-th percentile | 6975
Maximum | 9999
Range | 9999
Interquartile range (IQR) | 7

Descriptive statistics

Standard deviation | 2153.9028
Coefficient of variation (CV) | 2.7991263
Kurtosis | 6.3919647
Mean | 769.4911
Median Absolute Deviation (MAD) | 1
Skewness | 2.7753203
Sum | 216227
Variance | 4639297.3
Monotonicity | Not monotonic

Histogram with fixed size bins (bins=46)

Value | Count | Frequency (%)
0 | 140 | 4.1%
5 | 41 | 1.2%
6 | 11 | 0.3%
3 | 10 | 0.3%
8000 | 9 | 0.3%
5000 | 8 | 0.2%
7 | 8 | 0.2%
6000 | 5 | 0.1%
20 | 3 | 0.1%
10 | 3 | 0.1%
Other values (36) | 43 | 1.3%
(Missing) | 3117 | 91.7%

Value | Count | Frequency (%)
0 | 140 | 4.1%
1 | 1 | < 0.1%
2 | 1 | < 0.1%
3 | 10 | 0.3%
4 | 1 | < 0.1%
5 | 41 | 1.2%
6 | 11 | 0.3%
7 | 8 | 0.2%
8 | 2 | 0.1%
10 | 3 | 0.1%

Value | Count | Frequency (%)
9999 | 1 | < 0.1%
9000 | 3 | 0.1%
8000 | 9 | 0.3%
7000 | 1 | < 0.1%
6975 | 1 | < 0.1%
6000 | 5 | 0.1%
5293 | 1 | < 0.1%
5000 | 8 | 0.2%
4000 | 1 | < 0.1%
3300 | 1 | < 0.1%

# Interactions

# Correlations

| aware_of_no_of_units_generated_by_solar_system | capacity_of_the_solar_system | had_solar_energy_when_w2_was_done | increased_or_decreased_no_of_panels_after_w1 | installed_a_solar_system_after_w1 | no_of_units_generated_last_month | solar_energy_used_for_car_charging | solar_energy_used_for_cooking | solar_energy_used_for_water_heating | solar_system_inverter_or_non_inverter | solar_system_ongrid_or_offgrid | still_have_the_solar_system_from_w1
--- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ---
aware_of_no_of_units_generated_by_solar_system | 1.000 | 0.099 | 0.087 | 0.138 | 1.000 | 1.000 | 1.000 | 0.707 | 0.000 | 0.143 | 0.183 | 1.000
capacity_of_the_solar_system | 0.099 | 1.000 | 0.000 | 0.000 | 1.000 | 0.072 | 1.000 | 0.000 | 0.148 | 0.237 | 0.000 | 1.000
had_solar_energy_when_w2_was_done | 0.087 | 0.000 | 1.000 | 1.000 | 1.000 | 0.000 | 1.000 | 0.707 | 0.000 | 0.000 | 0.136 | 1.000
increased_or_decreased_no_of_panels_after_w1 | 0.138 | 0.000 | 1.000 | 1.000 | 0.000 | 0.440 | 1.000 | 1.000 | 0.024 | 0.029 | 0.158 | 1.000
installed_a_solar_system_after_w1 | 1.000 | 1.000 | 1.000 | 0.000 | 1.000 | 1.000 | 0.000 | NaN | 1.000 | 1.000 | 1.000 | 0.000
no_of_units_generated_last_month | 1.000 | 0.072 | 0.000 | 0.440 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 0.263 | 0.040 | 1.000
solar_energy_used_for_car_charging | 1.000 | 1.000 | 1.000 | 1.000 | 0.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000
solar_energy_used_for_cooking | 0.707 | 0.000 | 0.707 | 1.000 | NaN | 1.000 | 1.000 | 1.000 | 0.707 | 0.707 | 1.000 | 1.000
solar_energy_used_for_water_heating | 0.000 | 0.148 | 0.000 | 0.024 | 1.000 | 1.000 | 1.000 | 0.707 | 1.000 | 0.396 | 1.000 | 1.000
solar_system_inverter_or_non_inverter | 0.143 | 0.237 | 0.000 | 0.029 | 1.000 | 0.263 | 1.000 | 0.707 | 0.396 | 1.000 | 0.325 | 1.000
solar_system_ongrid_or_offgrid | 0.183 | 0.000 | 0.136 | 0.158 | 1.000 | 0.040 | 1.000 | 1.000 | 1.000 | 0.325 | 1.000 | 1.000
still_have_the_solar_system_from_w1 | 1.000 | 1.000 | 1.000 | 1.000 | 0.000 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 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 | had_solar_energy_when_w2_was_done | installed_a_solar_system_after_w1 | still_have_the_solar_system_from_w1 | increased_or_decreased_no_of_panels_after_w1 | solar_system_ongrid_or_offgrid | solar_system_inverter_or_non_inverter | solar_energy_used_for_water_heating | solar_energy_used_for_cooking | solar_energy_used_for_outdoor_lighting | solar_energy_used_for_car_charging | solar_energy_used_for_agricultural_systems | solar_energy_used_for_all_above | solar_energy_used_for_other_purposes | aware_of_no_of_units_generated_by_solar_system | no_of_units_generated_last_month | capacity_of_the_solar_system
--- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ---
0 | ID0726 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
1 | ID0734 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
2 | ID2795 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
3 | ID2829 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
4 | ID2843 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
5 | ID2906 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
6 | ID2908 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
7 | ID2917 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
8 | ID2836 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
9 | ID2915 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN

| household_ID | had_solar_energy_when_w2_was_done | installed_a_solar_system_after_w1 | still_have_the_solar_system_from_w1 | increased_or_decreased_no_of_panels_after_w1 | solar_system_ongrid_or_offgrid | solar_system_inverter_or_non_inverter | solar_energy_used_for_water_heating | solar_energy_used_for_cooking | solar_energy_used_for_outdoor_lighting | solar_energy_used_for_car_charging | solar_energy_used_for_agricultural_systems | solar_energy_used_for_all_above | solar_energy_used_for_other_purposes | aware_of_no_of_units_generated_by_solar_system | no_of_units_generated_last_month | capacity_of_the_solar_system
--- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | ---
3388 | ID3458 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
3389 | ID3064 | 1.0 | NaN | 1.0 | 3.0 | 1.0 | 1.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | 0.0 | NaN | 0.0
3390 | ID0586 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
3391 | ID0403 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
3392 | ID2268 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
3393 | ID1147 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
3394 | ID0963 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
3395 | ID1024 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
3396 | ID2440 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN
3397 | ID1050 | 2.0 | 2.0 | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN | NaN