******************Tables******************************************

FCS_DISTRICT/REGION

HDDS_DISTRICT/ REGION

HHS_DISTRICT/ REGION

LIVELIHOOD_DISTRICT/REGIONS

rCSI_DISTRICT/ REGIONS

Others

Occupation of Household heads

Sex of Household heads

Food source by Food Group

Staples

Legumes

Milk and dairy products

Protein

Vegetables

Fruits

Fats and oil

Sugar

Condiments

Food Source All Regions and Districts

Food based coping strategies by strategy

Food based coping strategies All, Districts and Regions

## Warning in merge.data.frame(merged_2, r.adult.meal, by = "ADMIN2Name", all.x =
## TRUE, : column names 'Total.x', 'Total.y' are duplicated in the result
## Warning in merge.data.frame(merged_3, r.number.meals, by = "ADMIN2Name", :
## column names 'Total.x', 'Total.y' are duplicated in the result
## Warning in merge.data.frame(merged_2.1, r.adult.meal.1, by = "ADMIN1Name", :
## column names 'Total.x', 'Total.y' are duplicated in the result
## Warning in merge.data.frame(merged_3.1, r.number.meals.1, by = "ADMIN1Name", :
## column names 'Total.x', 'Total.y' are duplicated in the result

Shocks_REGION

Shocks_DISTRICT/ REGION

shocks (40%+) by DISTRICT/ REGION

## `summarise()` has grouped output by 'Region'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'Region'. You can override using the
## `.groups` argument.