Apply to your Data 5
Jordan Lanowy
2024-10-10
library(tidyverse)## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.1
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(correlationfunnel)## ══ correlationfunnel Tip #3 ════════════════════════════════════════════════════
## Using `binarize()` with data containing many columns or many rows can increase dimensionality substantially.
## Try subsetting your data column-wise or row-wise to avoid creating too many columns.
## You can always make a big problem smaller by sampling. :)# Import Data
museums <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-11-22/museums.csv')## Rows: 4191 Columns: 35
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (24): museum_id, Name_of_museum, Address_line_1, Address_line_2, Village...
## dbl (11): Latitude, Longitude, DOMUS_identifier, Area_Deprivation_index, Are...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.skimr::skim(museums)| Name | museums |
| Number of rows | 4191 |
| Number of columns | 35 |
| _______________________ | |
| Column type frequency: | |
| character | 24 |
| numeric | 11 |
| ________________________ | |
| Group variables | None |
Variable type: character
| skim_variable | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
|---|---|---|---|---|---|---|---|
| museum_id | 0 | 1.00 | 8 | 15 | 0 | 4191 | 0 |
| Name_of_museum | 0 | 1.00 | 3 | 76 | 0 | 4190 | 0 |
| Address_line_1 | 441 | 0.89 | 3 | 61 | 0 | 3212 | 0 |
| Address_line_2 | 2816 | 0.33 | 3 | 39 | 0 | 1167 | 0 |
| Village,_Town_or_City | 4 | 1.00 | 3 | 24 | 0 | 1696 | 0 |
| Postcode | 0 | 1.00 | 6 | 9 | 0 | 3918 | 0 |
| Admin_area | 0 | 1.00 | 12 | 137 | 0 | 393 | 0 |
| Accreditation | 0 | 1.00 | 10 | 12 | 0 | 2 | 0 |
| Governance | 0 | 1.00 | 7 | 41 | 0 | 13 | 0 |
| Size | 0 | 1.00 | 4 | 7 | 0 | 5 | 0 |
| Size_provenance | 179 | 0.96 | 2 | 29 | 0 | 16 | 0 |
| Subject_Matter | 0 | 1.00 | 5 | 45 | 0 | 114 | 0 |
| Year_opened | 0 | 1.00 | 9 | 9 | 0 | 351 | 0 |
| Year_closed | 0 | 1.00 | 9 | 9 | 0 | 170 | 0 |
| DOMUS_Subject_Matter | 2788 | 0.33 | 5 | 27 | 0 | 21 | 0 |
| Primary_provenance_of_data | 0 | 1.00 | 3 | 8 | 0 | 18 | 0 |
| Identifier_used_in_primary_data_source | 2056 | 0.51 | 2 | 8 | 0 | 2134 | 0 |
| Area_Geodemographic_group | 49 | 0.99 | 11 | 40 | 0 | 17 | 0 |
| Area_Geodemographic_group_code | 49 | 0.99 | 3 | 3 | 0 | 16 | 0 |
| Area_Geodemographic_subgroup | 49 | 0.99 | 12 | 39 | 0 | 25 | 0 |
| Area_Geodemographic_subgroup_code | 49 | 0.99 | 4 | 4 | 0 | 24 | 0 |
| Area_Geodemographic_supergroup | 49 | 0.99 | 16 | 39 | 0 | 8 | 0 |
| Area_Geodemographic_supergroup_code | 49 | 0.99 | 2 | 2 | 0 | 8 | 0 |
| Notes | 2980 | 0.29 | 12 | 751 | 0 | 956 | 0 |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| Latitude | 0 | 1.00 | 52.93 | 2.09 | 49.18 | 51.48 | 52.47 | 53.96 | 100.00 | ▇▁▁▁▁ |
| Longitude | 0 | 1.00 | -1.96 | 1.84 | -8.09 | -3.10 | -1.87 | -0.48 | 1.76 | ▁▂▇▇▅ |
| DOMUS_identifier | 2347 | 0.44 | 1303.45 | 1597.19 | 1.00 | 486.50 | 991.50 | 1470.25 | 7746.00 | ▇▂▁▁▁ |
| Area_Deprivation_index | 49 | 0.99 | 5.44 | 2.48 | 1.00 | 4.00 | 5.00 | 7.00 | 10.00 | ▃▆▇▆▃ |
| Area_Deprivation_index_crime | 49 | 0.99 | 5.43 | 3.07 | 1.00 | 3.00 | 6.00 | 8.00 | 10.00 | ▇▆▅▇▇ |
| Area_Deprivation_index_education | 49 | 0.99 | 6.04 | 2.61 | 1.00 | 4.00 | 6.00 | 8.00 | 10.00 | ▃▅▇▇▆ |
| Area_Deprivation_index_employment | 49 | 0.99 | 6.08 | 2.76 | 1.00 | 4.00 | 6.00 | 8.00 | 10.00 | ▅▆▇▇▇ |
| Area_Deprivation_index_health | 49 | 0.99 | 6.02 | 2.82 | 1.00 | 4.00 | 6.00 | 8.00 | 10.00 | ▅▆▆▇▇ |
| Area_Deprivation_index_housing | 49 | 0.99 | 3.97 | 2.75 | 1.00 | 1.00 | 3.00 | 6.00 | 10.00 | ▇▅▃▂▂ |
| Area_Deprivation_index_income | 49 | 0.99 | 5.99 | 2.62 | 1.00 | 4.00 | 6.00 | 8.00 | 10.00 | ▃▆▇▇▆ |
| Area_Deprivation_index_services | 49 | 0.99 | 4.78 | 3.01 | 1.00 | 2.00 | 4.00 | 7.00 | 10.00 | ▇▅▅▅▅ |
missing values Addressline_2, Addressline_1, DOMUS_Subject_Matter, DOMUS_Identifier, Notes factors or numeric variables Zero Variance variables Character variables Unbalanced target variables id variable museum_id
museums %>% count(Accreditation)## # A tibble: 2 × 2
## Accreditation n
## <chr> <int>
## 1 Accredited 1720
## 2 Unaccredited 2471museums %>%
ggplot(aes(Accreditation)) +
geom_bar()
data <- museums %>%
select(-Address_line_1, -Address_line_2, -DOMUS_Subject_Matter,-DOMUS_identifier, -Notes, -Identifier_used_in_primary_data_source) %>%
na.omit()
skimr::skim(data)| Name | data |
| Number of rows | 3966 |
| Number of columns | 29 |
| _______________________ | |
| Column type frequency: | |
| character | 19 |
| numeric | 10 |
| ________________________ | |
| Group variables | None |
Variable type: character
| skim_variable | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
|---|---|---|---|---|---|---|---|
| museum_id | 0 | 1 | 10 | 15 | 0 | 3966 | 0 |
| Name_of_museum | 0 | 1 | 3 | 76 | 0 | 3965 | 0 |
| Village,_Town_or_City | 0 | 1 | 3 | 24 | 0 | 1639 | 0 |
| Postcode | 0 | 1 | 6 | 9 | 0 | 3725 | 0 |
| Admin_area | 0 | 1 | 16 | 137 | 0 | 392 | 0 |
| Accreditation | 0 | 1 | 10 | 12 | 0 | 2 | 0 |
| Governance | 0 | 1 | 7 | 41 | 0 | 13 | 0 |
| Size | 0 | 1 | 4 | 7 | 0 | 5 | 0 |
| Size_provenance | 0 | 1 | 2 | 29 | 0 | 16 | 0 |
| Subject_Matter | 0 | 1 | 5 | 45 | 0 | 112 | 0 |
| Year_opened | 0 | 1 | 9 | 9 | 0 | 334 | 0 |
| Year_closed | 0 | 1 | 9 | 9 | 0 | 159 | 0 |
| Primary_provenance_of_data | 0 | 1 | 3 | 8 | 0 | 17 | 0 |
| Area_Geodemographic_group | 0 | 1 | 11 | 40 | 0 | 17 | 0 |
| Area_Geodemographic_group_code | 0 | 1 | 3 | 3 | 0 | 16 | 0 |
| Area_Geodemographic_subgroup | 0 | 1 | 12 | 39 | 0 | 25 | 0 |
| Area_Geodemographic_subgroup_code | 0 | 1 | 4 | 4 | 0 | 24 | 0 |
| Area_Geodemographic_supergroup | 0 | 1 | 16 | 39 | 0 | 8 | 0 |
| Area_Geodemographic_supergroup_code | 0 | 1 | 2 | 2 | 0 | 8 | 0 |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| Latitude | 0 | 1 | 52.93 | 1.95 | 49.20 | 51.48 | 52.46 | 53.94 | 60.79 | ▅▇▃▁▁ |
| Longitude | 0 | 1 | -1.94 | 1.83 | -8.09 | -3.09 | -1.86 | -0.47 | 1.76 | ▁▂▇▇▅ |
| Area_Deprivation_index | 0 | 1 | 5.46 | 2.48 | 1.00 | 4.00 | 5.00 | 7.00 | 10.00 | ▃▆▇▆▃ |
| Area_Deprivation_index_crime | 0 | 1 | 5.43 | 3.07 | 1.00 | 3.00 | 6.00 | 8.00 | 10.00 | ▇▆▅▆▇ |
| Area_Deprivation_index_education | 0 | 1 | 6.05 | 2.61 | 1.00 | 4.00 | 6.00 | 8.00 | 10.00 | ▃▅▇▇▆ |
| Area_Deprivation_index_employment | 0 | 1 | 6.08 | 2.77 | 1.00 | 4.00 | 6.00 | 8.00 | 10.00 | ▅▆▇▇▇ |
| Area_Deprivation_index_health | 0 | 1 | 6.02 | 2.82 | 1.00 | 4.00 | 6.00 | 8.00 | 10.00 | ▅▆▆▇▇ |
| Area_Deprivation_index_housing | 0 | 1 | 3.99 | 2.76 | 1.00 | 1.00 | 3.00 | 6.00 | 10.00 | ▇▅▃▃▂ |
| Area_Deprivation_index_income | 0 | 1 | 6.00 | 2.63 | 1.00 | 4.00 | 6.00 | 8.00 | 10.00 | ▃▆▇▇▆ |
| Area_Deprivation_index_services | 0 | 1 | 4.79 | 3.01 | 1.00 | 2.00 | 4.00 | 8.00 | 10.00 | ▇▅▅▅▅ |
data %>%
ggplot(aes(Accreditation, Area_Deprivation_index_employment)) +
geom_boxplot()
data %>%
ggplot(aes(Accreditation, Area_Deprivation_index_crime)) +
geom_boxplot()
data %>%
ggplot(aes(Accreditation, Area_Deprivation_index_health)) +
geom_boxplot()
data_binarized <- data %>%
select(-museum_id) %>%
binarize()
data_binarized %>% glimpse()## Rows: 3,966
## Columns: 246
## $ `Name_of_museum__Public_Library_&_Museum_(Camborne)` <dbl> …
## $ `Name_of_museum__-OTHER` <dbl> …
## $ `Village,_Town_or_City__Edinburgh` <dbl> …
## $ `Village,_Town_or_City__London` <dbl> …
## $ `Village,_Town_or_City__-OTHER` <dbl> …
## $ Postcode__SO23_8TS <dbl> …
## $ `Postcode__-OTHER` <dbl> …
## $ `Latitude__-Inf_51.48120725` <dbl> …
## $ Latitude__51.48120725_52.4554475 <dbl> …
## $ Latitude__52.4554475_53.9431025 <dbl> …
## $ Latitude__53.9431025_Inf <dbl> …
## $ `Longitude__-Inf_-3.0854455` <dbl> …
## $ `Longitude__-3.0854455_-1.8564615` <dbl> …
## $ `Longitude__-1.8564615_-0.469075` <dbl> …
## $ `Longitude__-0.469075_Inf` <dbl> …
## $ `Admin_area__/England/London_(English_Region)/Westminster_(London_Borough)` <dbl> …
## $ `Admin_area__/England/South_West_(English_Region)/Cornwall_(English_UA)` <dbl> …
## $ `Admin_area__/England/South_West_(English_Region)/Wiltshire_(English_UA)` <dbl> …
## $ `Admin_area__/Scotland/City_of_Edinburgh_(Scottish_Council_Area)` <dbl> …
## $ `Admin_area__/Scotland/Dumfries_and_Galloway_(Scottish_Council_Area)` <dbl> …
## $ `Admin_area__/Scotland/Highland_(Scottish_Council_Area)` <dbl> …
## $ `Admin_area__-OTHER` <dbl> …
## $ Accreditation__Accredited <dbl> …
## $ Accreditation__Unaccredited <dbl> …
## $ `Governance__Government-Local_Authority` <dbl> …
## $ `Governance__Government-National` <dbl> …
## $ `Governance__Independent-English_Heritage` <dbl> …
## $ `Governance__Independent-National_Trust` <dbl> …
## $ `Governance__Independent-Not_for_profit` <dbl> …
## $ `Governance__Independent-Private` <dbl> …
## $ `Governance__Independent-Unknown` <dbl> …
## $ Governance__University <dbl> …
## $ Governance__Unknown <dbl> …
## $ `Governance__-OTHER` <dbl> …
## $ Size__large <dbl> …
## $ Size__medium <dbl> …
## $ Size__small <dbl> …
## $ Size__unknown <dbl> …
## $ `Size__-OTHER` <dbl> …
## $ Size_provenance__ace_size_designation <dbl> …
## $ Size_provenance__aim_size_designation <dbl> …
## $ Size_provenance__domus <dbl> …
## $ `Size_provenance__ma(fam)` <dbl> …
## $ Size_provenance__mm_manual_estimate_2018 <dbl> …
## $ Size_provenance__mm_prediction_random_forest <dbl> …
## $ Size_provenance__scottish_national_audit <dbl> …
## $ Size_provenance__unknown <dbl> …
## $ Size_provenance__visitbritain <dbl> …
## $ `Size_provenance__-OTHER` <dbl> …
## $ `Subject_Matter__Archaeology-Roman` <dbl> …
## $ `Subject_Matter__Arts-Fine_and_decorative_arts` <dbl> …
## $ `Subject_Matter__Buildings-Houses-Large_houses` <dbl> …
## $ `Subject_Matter__Buildings-Houses-Medium_houses` <dbl> …
## $ `Subject_Matter__Industry_and_manufacture-Mining_and_quarrying` <dbl> …
## $ `Subject_Matter__Leisure_and_sport-Toys_and_models` <dbl> …
## $ Subject_Matter__Local_Histories <dbl> …
## $ `Subject_Matter__Mixed-Encyclopaedic` <dbl> …
## $ `Subject_Matter__Mixed-Other` <dbl> …
## $ Subject_Matter__Other <dbl> …
## $ `Subject_Matter__Personality-Literary` <dbl> …
## $ `Subject_Matter__Rural_Industry-Farming` <dbl> …
## $ `Subject_Matter__Sea_and_seafaring-Boats_and_ships` <dbl> …
## $ `Subject_Matter__Sea_and_seafaring-Mixed` <dbl> …
## $ `Subject_Matter__Transport-Cars_and_motorbikes` <dbl> …
## $ `Subject_Matter__Transport-Trains_and_railways` <dbl> …
## $ `Subject_Matter__War_and_conflict-Airforce` <dbl> …
## $ `Subject_Matter__War_and_conflict-Castles_and_forts` <dbl> …
## $ `Subject_Matter__War_and_conflict-Military` <dbl> …
## $ `Subject_Matter__War_and_conflict-Regiment` <dbl> …
## $ `Subject_Matter__-OTHER` <dbl> …
## $ `Year_opened__1945:1960` <dbl> …
## $ `Year_opened__1960:2017` <dbl> …
## $ `Year_opened__1972:1972` <dbl> …
## $ `Year_opened__1973:1973` <dbl> …
## $ `Year_opened__1974:1974` <dbl> …
## $ `Year_opened__1975:1975` <dbl> …
## $ `Year_opened__1976:1976` <dbl> …
## $ `Year_opened__1977:1977` <dbl> …
## $ `Year_opened__1978:1978` <dbl> …
## $ `Year_opened__1979:1979` <dbl> …
## $ `Year_opened__1980:1980` <dbl> …
## $ `Year_opened__1981:1981` <dbl> …
## $ `Year_opened__1982:1982` <dbl> …
## $ `Year_opened__1983:1983` <dbl> …
## $ `Year_opened__1984:1984` <dbl> …
## $ `Year_opened__1985:1985` <dbl> …
## $ `Year_opened__1986:1986` <dbl> …
## $ `Year_opened__1987:1987` <dbl> …
## $ `Year_opened__1988:1988` <dbl> …
## $ `Year_opened__1989:1989` <dbl> …
## $ `Year_opened__1990:1990` <dbl> …
## $ `Year_opened__1991:1991` <dbl> …
## $ `Year_opened__1992:1992` <dbl> …
## $ `Year_opened__1993:1993` <dbl> …
## $ `Year_opened__1994:1994` <dbl> …
## $ `Year_opened__1995:1995` <dbl> …
## $ `Year_opened__1996:1996` <dbl> …
## $ `Year_opened__1997:1997` <dbl> …
## $ `Year_opened__1999:1999` <dbl> …
## $ `Year_opened__2000:2000` <dbl> …
## $ `Year_opened__2001:2001` <dbl> …
## $ `Year_opened__2005:2005` <dbl> …
## $ `Year_opened__-OTHER` <dbl> …
## $ `Year_closed__9999:9999` <dbl> …
## $ `Year_closed__-OTHER` <dbl> …
## $ Primary_provenance_of_data__ace <dbl> …
## $ Primary_provenance_of_data__aim <dbl> …
## $ Primary_provenance_of_data__aim82M <dbl> …
## $ Primary_provenance_of_data__aim82NM <dbl> …
## $ Primary_provenance_of_data__domus <dbl> …
## $ Primary_provenance_of_data__fcm <dbl> …
## $ Primary_provenance_of_data__hha <dbl> …
## $ Primary_provenance_of_data__mald <dbl> …
## $ Primary_provenance_of_data__mgs <dbl> …
## $ Primary_provenance_of_data__misc <dbl> …
## $ Primary_provenance_of_data__musassoc <dbl> …
## $ Primary_provenance_of_data__wiki <dbl> …
## $ `Primary_provenance_of_data__-OTHER` <dbl> …
## $ `Area_Deprivation_index__-Inf_4` <dbl> …
## $ Area_Deprivation_index__4_5 <dbl> …
## $ Area_Deprivation_index__5_7 <dbl> …
## $ Area_Deprivation_index__7_Inf <dbl> …
## $ `Area_Deprivation_index_crime__-Inf_3` <dbl> …
## $ Area_Deprivation_index_crime__3_6 <dbl> …
## $ Area_Deprivation_index_crime__6_8 <dbl> …
## $ Area_Deprivation_index_crime__8_Inf <dbl> …
## $ `Area_Deprivation_index_education__-Inf_4` <dbl> …
## $ Area_Deprivation_index_education__4_6 <dbl> …
## $ Area_Deprivation_index_education__6_8 <dbl> …
## $ Area_Deprivation_index_education__8_Inf <dbl> …
## $ `Area_Deprivation_index_employment__-Inf_4` <dbl> …
## $ Area_Deprivation_index_employment__4_6 <dbl> …
## $ Area_Deprivation_index_employment__6_8 <dbl> …
## $ Area_Deprivation_index_employment__8_Inf <dbl> …
## $ `Area_Deprivation_index_health__-Inf_4` <dbl> …
## $ Area_Deprivation_index_health__4_6 <dbl> …
## $ Area_Deprivation_index_health__6_8 <dbl> …
## $ Area_Deprivation_index_health__8_Inf <dbl> …
## $ `Area_Deprivation_index_housing__-Inf_3` <dbl> …
## $ Area_Deprivation_index_housing__3_6 <dbl> …
## $ Area_Deprivation_index_housing__6_Inf <dbl> …
## $ `Area_Deprivation_index_income__-Inf_4` <dbl> …
## $ Area_Deprivation_index_income__4_6 <dbl> …
## $ Area_Deprivation_index_income__6_8 <dbl> …
## $ Area_Deprivation_index_income__8_Inf <dbl> …
## $ `Area_Deprivation_index_services__-Inf_2` <dbl> …
## $ Area_Deprivation_index_services__2_4 <dbl> …
## $ Area_Deprivation_index_services__4_8 <dbl> …
## $ Area_Deprivation_index_services__8_Inf <dbl> …
## $ Area_Geodemographic_group__Country_Living <dbl> …
## $ Area_Geodemographic_group__English_and_Welsh_Countryside <dbl> …
## $ Area_Geodemographic_group__Ethnically_Diverse_Metropolitan_Living <dbl> …
## $ Area_Geodemographic_group__Larger_Towns_and_Cities <dbl> …
## $ Area_Geodemographic_group__London_Cosmopolitan <dbl> …
## $ Area_Geodemographic_group__Manufacturing_Traits <dbl> …
## $ Area_Geodemographic_group__Northern_Ireland_Countryside <dbl> …
## $ Area_Geodemographic_group__Remoter_Coastal_Living <dbl> …
## $ `Area_Geodemographic_group__Rural-Urban_Fringe` <dbl> …
## $ Area_Geodemographic_group__Scottish_Countryside <dbl> …
## $ Area_Geodemographic_group__Scottish_Industrial_Heritage <dbl> …
## $ Area_Geodemographic_group__Services_Manufacturing_and_Mining_Legacy <dbl> …
## $ Area_Geodemographic_group__Suburban_Traits <dbl> …
## $ Area_Geodemographic_group__Thriving_Rural <dbl> …
## $ Area_Geodemographic_group__Town_Living <dbl> …
## $ Area_Geodemographic_group__University_Towns_and_Cities <dbl> …
## $ `Area_Geodemographic_group__-OTHER` <dbl> …
## $ Area_Geodemographic_group_code__1ar <dbl> …
## $ Area_Geodemographic_group_code__1br <dbl> …
## $ Area_Geodemographic_group_code__2ar <dbl> …
## $ Area_Geodemographic_group_code__2br <dbl> …
## $ Area_Geodemographic_group_code__3ar <dbl> …
## $ Area_Geodemographic_group_code__3br <dbl> …
## $ Area_Geodemographic_group_code__3cr <dbl> …
## $ Area_Geodemographic_group_code__4ar <dbl> …
## $ Area_Geodemographic_group_code__5ar <dbl> …
## $ Area_Geodemographic_group_code__6ar <dbl> …
## $ Area_Geodemographic_group_code__6br <dbl> …
## $ Area_Geodemographic_group_code__7ar <dbl> …
## $ Area_Geodemographic_group_code__7br <dbl> …
## $ Area_Geodemographic_group_code__7cr <dbl> …
## $ Area_Geodemographic_group_code__8ar <dbl> …
## $ Area_Geodemographic_group_code__8br <dbl> …
## $ Area_Geodemographic_subgroup__Affluent_rural <dbl> …
## $ Area_Geodemographic_subgroup__Ageing_Coastal_Living <dbl> …
## $ Area_Geodemographic_subgroup__City_Periphery <dbl> …
## $ Area_Geodemographic_subgroup__Country_Living <dbl> …
## $ Area_Geodemographic_subgroup__Ethnically_Diverse_Metropolitan_Living <dbl> …
## $ Area_Geodemographic_subgroup__Expanding_Areas <dbl> …
## $ `Area_Geodemographic_subgroup__Industrial_and_Multi-ethnic` <dbl> …
## $ Area_Geodemographic_subgroup__Larger_Towns_and_Cities <dbl> …
## $ Area_Geodemographic_subgroup__London_Cosmopolitan <dbl> …
## $ Area_Geodemographic_subgroup__Manufacturing_Legacy <dbl> …
## $ Area_Geodemographic_subgroup__Mining_Legacy <dbl> …
## $ Area_Geodemographic_subgroup__Northern_Ireland_Countryside <dbl> …
## $ Area_Geodemographic_subgroup__Older_Farming_Communities <dbl> …
## $ Area_Geodemographic_subgroup__Prosperous_Towns <dbl> …
## $ Area_Geodemographic_subgroup__Rural_Growth_Areas <dbl> …
## $ `Area_Geodemographic_subgroup__Rural-Urban_Fringe` <dbl> …
## $ Area_Geodemographic_subgroup__Scottish_Countryside <dbl> …
## $ Area_Geodemographic_subgroup__Scottish_Industrial_Legacy <dbl> …
## $ Area_Geodemographic_subgroup__Seaside_Living <dbl> …
## $ Area_Geodemographic_subgroup__Service_Economy <dbl> …
## $ Area_Geodemographic_subgroup__Sparse_English_and_Welsh_Countryside <dbl> …
## $ Area_Geodemographic_subgroup__University_Towns_and_Cities <dbl> …
## $ Area_Geodemographic_subgroup__Urban_Living <dbl> …
## $ `Area_Geodemographic_subgroup__-OTHER` <dbl> …
## $ Area_Geodemographic_subgroup_code__1a1r <dbl> …
## $ Area_Geodemographic_subgroup_code__1b1r <dbl> …
## $ Area_Geodemographic_subgroup_code__1b2r <dbl> …
## $ Area_Geodemographic_subgroup_code__2a1r <dbl> …
## $ Area_Geodemographic_subgroup_code__2b1r <dbl> …
## $ Area_Geodemographic_subgroup_code__3a1r <dbl> …
## $ Area_Geodemographic_subgroup_code__3a2r <dbl> …
## $ Area_Geodemographic_subgroup_code__3b1r <dbl> …
## $ Area_Geodemographic_subgroup_code__3b2r <dbl> …
## $ Area_Geodemographic_subgroup_code__3c1r <dbl> …
## $ Area_Geodemographic_subgroup_code__4a1r <dbl> …
## $ Area_Geodemographic_subgroup_code__5a1r <dbl> …
## $ Area_Geodemographic_subgroup_code__6a1r <dbl> …
## $ Area_Geodemographic_subgroup_code__6a2r <dbl> …
## $ Area_Geodemographic_subgroup_code__6a3r <dbl> …
## $ Area_Geodemographic_subgroup_code__6b1r <dbl> …
## $ Area_Geodemographic_subgroup_code__7a1r <dbl> …
## $ Area_Geodemographic_subgroup_code__7b1r <dbl> …
## $ Area_Geodemographic_subgroup_code__7c2r <dbl> …
## $ Area_Geodemographic_subgroup_code__8a1r <dbl> …
## $ Area_Geodemographic_subgroup_code__8a2r <dbl> …
## $ Area_Geodemographic_subgroup_code__8b1r <dbl> …
## $ Area_Geodemographic_subgroup_code__8b2r <dbl> …
## $ `Area_Geodemographic_subgroup_code__-OTHER` <dbl> …
## $ Area_Geodemographic_supergroup__Affluent_England <dbl> …
## $ Area_Geodemographic_supergroup__Business_Education_and_Heritage_Centres <dbl> …
## $ Area_Geodemographic_supergroup__Countryside_Living <dbl> …
## $ Area_Geodemographic_supergroup__Ethnically_Diverse_Metropolitan_Living <dbl> …
## $ Area_Geodemographic_supergroup__London_Cosmopolitan <dbl> …
## $ Area_Geodemographic_supergroup__Services_and_Industrial_Legacy <dbl> …
## $ Area_Geodemographic_supergroup__Town_and_Country_Living <dbl> …
## $ Area_Geodemographic_supergroup__Urban_Settlements <dbl> …
## $ Area_Geodemographic_supergroup_code__1r <dbl> …
## $ Area_Geodemographic_supergroup_code__2r <dbl> …
## $ Area_Geodemographic_supergroup_code__3r <dbl> …
## $ Area_Geodemographic_supergroup_code__4r <dbl> …
## $ Area_Geodemographic_supergroup_code__5r <dbl> …
## $ Area_Geodemographic_supergroup_code__6r <dbl> …
## $ Area_Geodemographic_supergroup_code__7r <dbl> …
## $ Area_Geodemographic_supergroup_code__8r <dbl> …data_correlate <- data_binarized %>%
correlate(Accreditation__Accredited)
data_correlate %>%
correlationfunnel::plot_correlation_funnel()## Warning: ggrepel: 236 unlabeled data points (too many overlaps). Consider
## increasing max.overlaps