| Type: | Package |
| Title: | Data Manipulation |
| Version: | 1.2.0 |
| Author: | Seyma Kalay |
| Maintainer: | Seyma Kalay <seymakalay@hotmail.com> |
| Description: | Is designed to make easier printing summary statistics (for continues and factor level) tables in Latex, and plotting by factor. |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.1.2 |
| URL: | https://github.com/seymakalay/pepe |
| BugReports: | https://github.com/seymakalay/pepe/issues |
| Suggests: | knitr, rmarkdown |
| VignetteBuilder: | knitr |
| Depends: | R (≥ 2.10) |
| Imports: | dplyr, ggplot2, psych, tidyr, utils |
| NeedsCompilation: | no |
| Packaged: | 2022-05-12 14:26:14 UTC; Seyma |
| Repository: | CRAN |
| Date/Publication: | 2022-05-13 16:40:02 UTC |
Plot by Factor
Description
Plot by Factor
Usage
Plot.by.Factr(XXX, name.levels)
Arguments
XXX |
object to be plotted. |
name.levels |
name object. |
Value
The output from Plot.by.Factr.
Examples
df <- sample_data[c("Formal","Informal","L.Both",
"No.Loan", "sex","educ","political.afl","married",
"havejob","rural","age","Income","Networth","Liquid.Assets",
"NW.HE","fin.knowldge","fin.intermdiaries")]
CN = colnames(df)
var <- c("educ","rural")
name.levels <- c("Formal","Informal","L.Both","No.Loan",
"sex","educ","political.afl","married",
"havejob","rural","age","Income","Networth","Liquid.Assets",
"NW.HE","fin.knowldge","fin.intermdiaries")
XXX <- df4.Plot.by.Factr(var,df)$Summ.Stats.long
Plot.by.Factr(XXX, name.levels)
Pivot Table by Factor
Description
Pivot Table by Factor
Usage
Pvot.by.Factr(df)
Arguments
df |
The data frame of factor variables. |
Value
The output from Pvot.by.Factr.
Examples
df <- sample_data[c("multi.level",
"Formal","L.Both","No.Loan",
"region", "sex", "educ", "political.afl",
"married", "havejob", "rural",
"fin.knowldge", "fin.intermdiaries")]
Pvot.by.Factr(df)
Summary Statistics by Factor
Description
Summary Statistics by Factor
Usage
Stats.by.Factr(var, df)
Arguments
var |
The vector to set summary statistics. |
df |
The name of the Data set. |
Value
The output from Stats.by.Factr.
Examples
df <- sample_data[c("Formal","Informal","L.Both","No.Loan",
"sex","educ","political.afl","married",
"havejob","rural","age","Income","Networth","Liquid.Assets",
"NW.HE","fin.knowldge","fin.intermdiaries")]
CN = colnames(df)
var <- c("educ","rural")
Stats.by.Factr(var, df)
Creating Dataset for Plot.by.Factr
Description
Creating Dataset for Plot.by.Factr
Usage
df4.Plot.by.Factr(var, df)
Arguments
var |
Vector of factor variables. |
df |
Dataset. |
Value
The output from df4.Plot.by.Factr
Examples
df <- sample_data[c("Formal","Informal","L.Both","No.Loan",
"sex","educ","political.afl","married",
"havejob","rural","age","Income","Networth","Liquid.Assets",
"NW.HE","fin.knowldge","fin.intermdiaries")]
CN = colnames(df)
var <- c("educ", "rural", "sex", "havejob", "political.afl")
df4.Plot.by.Factr(var,df)
pepe package
Description
See the README on GitHub
Sample data for analysis. A dataset containing information of access to credit.
Description
Sample data for analysis.
A dataset containing information of access to credit.
Usage
sample_data
Format
A data_frame with 53940 rows and 10 variables:
- hhid
hhid, household id number
- Cluster.No
Cluster.No, cluster no
- region
region, 3 factor level, west, east, and center
- No.Loan
No.Loan, if the household has no loan
- Formal
Formal, if the household has formal loan
- Both
Both, if the household has both loan
- Informal
Informal, if the household has informal loan
- sex
sex, if the household has male
- Income
Income of the household
- Loan.Type
Loan.Type, 4 factor level type of the loan
- multi.level
multi.level, 2 factor level if the household has access to loan or not
...