BUSINESS PRACTICES
df_corr <- df %>% select(
bp_advert_b,
bp_screen_b,
bp_dec_flex,
bp_dec_standard,
bp_dec_offer,
bp_vouch_b,
bp_crim_b,
bp_dis_b,
bp_keep_pct_num,
bp_keep_rsn,
bp_install_b,
bp_comm_unit_fee_app_b,
bp_comm_unit_fee_sec_b,
bp_comm_unit_fee_clean_b,
bp_comm_unit_fee_park_b,
bp_fair,
bp_comm_unit_fee_incl_b,
bp_comm_unit_deposit_b,
bp_rent_raise_b)
df_corr <- df_corr %>% rename("App fee" = bp_comm_unit_fee_app_b,
"Security deposit" = bp_comm_unit_fee_sec_b,
"Cleaning fee" = bp_comm_unit_fee_clean_b,
"Parking fee" = bp_comm_unit_fee_park_b,
"Advertising" = bp_advert_b,
"Screening" = bp_screen_b,
"Flexible decision" = bp_dec_flex,
"Standard criteria" = bp_dec_standard,
"Offers to nonstandard" = bp_dec_offer,
"Rent to vouchers" = bp_vouch_b,
"Rent to criminal" = bp_crim_b,
"Disability accom." = bp_dis_b,
"Deposit pct. kept" = bp_keep_pct_num,
"Depsoit kept reason" = bp_keep_rsn,
"Allow installments" = bp_install_b,
"Fair market price" = bp_fair,
"Utilities included" = bp_comm_unit_fee_incl_b,
"Last month required" = bp_comm_unit_deposit_b,
"Raised rent" = bp_rent_raise_b)
df_corr1 <- df_corr %>%
select("Advertising",
"Screening",
"Flexible decision",
"Standard criteria" ,
"Offers to nonstandard",
"App fee",
"Security deposit",
"Cleaning fee",
"Parking fee")
df_corr2 <- df_corr %>%
select("Advertising",
"Screening",
"Flexible decision",
"Standard criteria" ,
"Offers to nonstandard",
"Rent to vouchers",
"Rent to criminal",
"Disability accom.")
df_corr3 <- df_corr %>%
select("App fee",
"Security deposit",
"Cleaning fee",
"Parking fee",
"Rent to vouchers",
"Rent to criminal",
"Disability accom.")
df_corr4 <- df_corr %>%
select("App fee",
"Security deposit",
"Cleaning fee",
"Parking fee",
"Deposit pct. kept" ,
"Depsoit kept reason",
"Allow installments",
"Fair market price",
"Utilities included",
"Last month required",
"Raised rent")
df_corr5 <- df_corr %>%
select("Rent to vouchers",
"Rent to criminal",
"Disability accom.",
"Deposit pct. kept" ,
"Depsoit kept reason",
"Allow installments",
"Fair market price",
"Utilities included",
"Last month required",
"Raised rent")
df_corr6 <- df_corr %>%
select("Advertising",
"Screening",
"Flexible decision",
"Standard criteria" ,
"Offers to nonstandard",
"Deposit pct. kept" ,
"Depsoit kept reason",
"Allow installments",
"Fair market price",
"Utilities included",
"Last month required",
"Raised rent")
#
# library(ggcorrplot)
# model.matrix(~0+., data=df_corr) %>%
# cor(use="pairwise.complete.obs") %>%
# ggcorrplot(
# show.diag = F,
# type="lower",
# lab=TRUE,
# lab_size=1) +
# theme(axis.text.x = element_text(angle=90, size = 6)) +
# theme(axis.text.y = element_text(size = 6) )
#
library(ggcorrplot)
model.matrix(~0+., data=df_corr1) %>%
cor(use="pairwise.complete.obs") %>%
ggcorrplot(
show.diag = F,
type="lower",
lab=TRUE,
lab_size=1.5) +
theme(axis.text.x = element_text(angle=90, size = 6)) +
theme(axis.text.y = element_text(size = 6) )
## Warning in cor(., use = "pairwise.complete.obs"): the standard deviation is zero
library(ggcorrplot)
model.matrix(~0+., data=df_corr2) %>%
cor(use="pairwise.complete.obs") %>%
ggcorrplot(
show.diag = F,
type="lower",
lab=TRUE,
lab_size=1.4) +
theme(axis.text.x = element_text(angle=90, size = 6)) +
theme(axis.text.y = element_text(size = 6) )
## Warning in cor(., use = "pairwise.complete.obs"): the standard deviation is zero
library(ggcorrplot)
model.matrix(~0+., data=df_corr3) %>%
cor(use="pairwise.complete.obs") %>%
ggcorrplot(
show.diag = F,
type="lower",
lab=TRUE,
lab_size=1.5) +
theme(axis.text.x = element_text(angle=90, size = 6)) +
theme(axis.text.y = element_text(size = 6) )
library(ggcorrplot)
model.matrix(~0+., data=df_corr4) %>%
cor(use="pairwise.complete.obs") %>%
ggcorrplot(
show.diag = F,
type="lower",
lab=TRUE,
lab_size=1.5) +
theme(axis.text.x = element_text(angle=90, size = 6)) +
theme(axis.text.y = element_text(size = 6) )
## Warning in cor(., use = "pairwise.complete.obs"): the standard deviation is zero
library(ggcorrplot)
model.matrix(~0+., data=df_corr5) %>%
cor(use="pairwise.complete.obs") %>%
ggcorrplot(
show.diag = F,
type="lower",
lab=TRUE,
lab_size=1.5) +
theme(axis.text.x = element_text(angle=90, size = 6)) +
theme(axis.text.y = element_text(size = 6) )
## Warning in cor(., use = "pairwise.complete.obs"): the standard deviation is zero
library(ggcorrplot)
model.matrix(~0+., data=df_corr6) %>%
cor(use="pairwise.complete.obs") %>%
ggcorrplot(
show.diag = F,
type="lower",
lab=TRUE,
lab_size=1.5) +
theme(axis.text.x = element_text(angle=90, size = 6)) +
theme(axis.text.y = element_text(size = 6) )
## Warning in cor(., use = "pairwise.complete.obs"): the standard deviation is zero
corr_cross(df_corr, # name of dataset
max_pvalue = 0.05, # display only significant correlations (at 5% level)
)
## Warning in corr_cross(df_corr, max_pvalue = 0.05, ): There are NA values in your
## data!
## Warning in cor(x, y): the standard deviation is zero
## Warning in cor(x, y): the standard deviation is zero
## Warning in cor(x, y): the standard deviation is zero
## Warning in cor(x, y): the standard deviation is zero
## Warning in cor(x, y): the standard deviation is zero
## Warning in cor(x, y): the standard deviation is zero
## Warning in .font_global(font, quiet = FALSE): Font 'Arial Narrow' is not
## installed, has other name, or can't be found
