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## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.4
## ✔ 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 errors
## Warning: package 'janitor' was built under R version 4.3.3
## 
## Attaching package: 'janitor'
## 
## The following objects are masked from 'package:stats':
## 
##     chisq.test, fisher.test
## 
## ℹ Suitable tokens found in the cache, associated with these emails:
## • 'aomutobe@dotrust.org'
## • 'omutove@gmail.com'
## • 'ookostephen8@gmail.com'
##   Defaulting to the first email.
## ! Using an auto-discovered, cached token.
##   To suppress this message, modify your code or options to clearly consent to
##   the use of a cached token.
##   See gargle's "Non-interactive auth" vignette for more details:
##   <https://gargle.r-lib.org/articles/non-interactive-auth.html>
## ℹ The googlesheets4 package is using a cached token for 'aomutobe@dotrust.org'.
## Auto-refreshing stale OAuth token.
## ✔ Reading from "Master_D_T_S database".
## ✔ Range ''All Data''.
## # A tibble: 6 × 9
##   Country Program              `Unique ID` Gender Age       `Program Start Date`
##   <chr>   <chr>                <chr>       <chr>  <list>    <list>              
## 1 Ghana   Community Leadership GNACLDTS1   Male   <dbl [1]> <chr [1]>           
## 2 Ghana   Community Leadership GNACLDTS10  Female <dbl [1]> <chr [1]>           
## 3 Ghana   Community Leadership GNACLDTS11  Male   <dbl [1]> <chr [1]>           
## 4 Ghana   Community Leadership GNACLDTS12  Male   <dbl [1]> <chr [1]>           
## 5 Ghana   Community Leadership GNACLDTS13  Male   <dbl [1]> <chr [1]>           
## 6 Ghana   Community Leadership GNACLDTS14  Female <dbl [1]> <chr [1]>           
## # ℹ 3 more variables: `Program End Date` <list>, Region <chr>, City <chr>
## [1] "Country"            "Program"            "Unique ID"         
## [4] "Gender"             "Age"                "Program Start Date"
## [7] "Program End Date"   "Region"             "City"
## [1] "Community Leaders"           "Digital Business"           
## [3] "Digital Jobs"                "Social Entrepreneur"        
## [5] "Street Teams"                "YLAB"                       
## [7] "Social Enterprise Prototype" "Social Enterprise MVP"      
## [9] "YLAB & Street team"
## [1] "Man"   "Woman" "Other"
##  [1] "Community Leadership"        "Digital Business"           
##  [3] "Digital Jobs Level 1"        "Digital Jobs Level 2"       
##  [5] "Social Entreprise"           "Street Teams"               
##  [7] "YLAB"                        "Digital Jobs Level 1 & 2"   
##  [9] "Social Enterprise Prototype" "Social Enterprise MVP"      
## [11] "YLAB/Street team"
## [1] "Male"              "Female"            "Prefer not to say"
## [4] "female"            "male"              "MALE"             
## [7] "FEMALE"
## [1] "Country"            "Program"            "Unique ID"         
## [4] "Gender"             "Age"                "Program Start Date"
## [7] "Program End Date"   "Region"             "City"
## `summarise()` has grouped output by 'Country'. You can override using the
## `.groups` argument.
##                      Program Ghana Jordan Kenya Lebanon Malawi Rwanda Tanzania
##            Community Leaders    20     90    79      55     13    136       97
##             Digital Business   207      0  2602     113    115   7551     8559
##                 Digital Jobs   842   5347 11159    3406    238      0      946
##          Social Entrepreneur    41    129     0       0      0      0       50
##                 Street Teams    13     14    26      13      6     64       11
##                         YLAB     0     18    15       7      0     12        8
##        Social Enterprise MVP     0      0    17       0      0     10        0
##  Social Enterprise Prototype     0      0    29       0      0     40        0
##           YLAB & Street team     0      0     3       0      0      0        0
##                        Total  1123   5598 13930    3594    372   7813     9671
##  Uganda Zambia Total
##      46      0   536
##    1814      0 20961
##    2252      0 24190
##       0      0   220
##      18      6   171
##       0      0    60
##       0      0    27
##       0      0    69
##       0      0     3
##    4130      6 46237
## `summarise()` has grouped output by 'Gender'. You can override using the
## `.groups` argument.