library(rio)

DENUNCIAS = import("https://docs.google.com/spreadsheets/d/1ske_yHt4tOcCK0h1aPZnd2EP6zM9Sv8Q/edit#gid=40790052")
head(DENUNCIAS)
##                                                         V1    V2    V3
## 1 TASA DE DENUNCIAS POR COMISION DE DELITOS,SEGUN DISTRITO            
## 2                        (Tasa por cada 10 000 habitantes)            
## 3                                                                     
## 4                                                          Per?o  2022
## 5                                                 Distrito            
## 6                                              150101 LIMA       642,7
RESIDUOS = import("residuosPeru.xlsx")
## New names:
## • `` -> `...2`
## • `` -> `...3`
## • `` -> `...4`
## • `` -> `...5`
## • `` -> `...6`
## • `` -> `...7`
## • `` -> `...8`
## • `` -> `...9`
## • `` -> `...10`
## • `` -> `...11`
## • `` -> `...12`
## • `` -> `...13`
## • `` -> `...14`
## • `` -> `...15`
head(RESIDUOS)
##   Residuos municipales generados anualmente  ...2   ...3    ...4         ...5
## 1                               FECHA_CORTE N_SEC UBIGEO REG_NAT DEPARTAMENTO
## 2                                  20230614     1  10101   SELVA     AMAZONAS
## 3                                  20230614     2  10102   SELVA     AMAZONAS
## 4                                  20230614     3  10103  SIERRA     AMAZONAS
## 5                                  20230614     4  10104  SIERRA     AMAZONAS
## 6                                  20230614     5  10105  SIERRA     AMAZONAS
##          ...6        ...7      ...8       ...9     ...10   ...11
## 1   PROVINCIA    DISTRITO POB_TOTAL POB_URBANA POB_RURAL GPC_DOM
## 2 CHACHAPOYAS CHACHAPOYAS     28423      27548       875    0.48
## 3 CHACHAPOYAS    ASUNCION       291        151       140    0.61
## 4 CHACHAPOYAS      BALSAS      1615        299      1316    0.45
## 5 CHACHAPOYAS       CHETO       597        388       209    0.45
## 6 CHACHAPOYAS   CHILIQUIN       737        197       540    0.45
##                ...12              ...13         ...14   ...15
## 1      QRESIDUOS_DOM   QRESIDUOS_NO_DOM QRESIDUOS_MUN PERIODO
## 2             4857.5 2081.7800000000002       6939.28    2014
## 3              33.56              14.38         47.95    2014
## 4              48.96              20.98         69.95    2014
## 5              63.59              27.25         90.84    2014
## 6 32.380000000000003              13.88         46.26    2014
# Eliminar las primeras 5 filas
DATADENUN<- DENUNCIAS[-(1:5), ]
library(stringr)
str_split(string = DATADENUN$V1,
          pattern = ' ')
## [[1]]
## [1] "150101" "LIMA"  
## 
## [[2]]
## [1] "150102" "ANCON" 
## 
## [[3]]
## [1] "150103" "ATE"   
## 
## [[4]]
## [1] "150104"   "BARRANCO"
## 
## [[5]]
## [1] "150105" "BREс"  
## 
## [[6]]
## [1] "150106"     "CARABAYLLO"
## 
## [[7]]
## [1] "150107"     "CHACLACAYO"
## 
## [[8]]
## [1] "150108"     "CHORRILLOS"
## 
## [[9]]
## [1] "150109"      "CIENEGUILLA"
## 
## [[10]]
## [1] "150110" "COMAS" 
## 
## [[11]]
## [1] "150111"   "EL"       "AGUSTINO"
## 
## [[12]]
## [1] "150112"        "INDEPENDENCIA"
## 
## [[13]]
## [1] "150113" "JESUS"  "MARIA" 
## 
## [[14]]
## [1] "150114" "LA"     "MOLINA"
## 
## [[15]]
## [1] "150115"   "LA"       "VICTORIA"
## 
## [[16]]
## [1] "150116" "LINCE" 
## 
## [[17]]
## [1] "150117" "LOS"    "OLIVOS"
## 
## [[18]]
## [1] "150118"     "LURIGANCHO"
## 
## [[19]]
## [1] "150119" "LURIN" 
## 
## [[20]]
## [1] "150120"    "MAGDALENA" "DEL"       "MAR"      
## 
## [[21]]
## [1] "150121" "PUEBLO" "LIBRE" 
## 
## [[22]]
## [1] "150122"     "MIRAFLORES"
## 
## [[23]]
## [1] "150123"     "PACHACAMAC"
## 
## [[24]]
## [1] "150124"   "PUCUSANA"
## 
## [[25]]
## [1] "150125" "PUENTE" "PIEDRA"
## 
## [[26]]
## [1] "150126"  "PUNTA"   "HERMOSA"
## 
## [[27]]
## [1] "150127" "PUNTA"  "NEGRA" 
## 
## [[28]]
## [1] "150128" "RIMAC" 
## 
## [[29]]
## [1] "150129"  "SAN"     "BARTOLO"
## 
## [[30]]
## [1] "150130" "SAN"    "BORJA" 
## 
## [[31]]
## [1] "150131" "SAN"    "ISIDRO"
## 
## [[32]]
## [1] "150132"     "SAN"        "JUAN"       "DE"         "LURIGANCHO"
## 
## [[33]]
## [1] "150133"     "SAN"        "JUAN"       "DE"         "MIRAFLORES"
## 
## [[34]]
## [1] "150134" "SAN"    "LUIS"  
## 
## [[35]]
## [1] "150135" "SAN"    "MARTIN" "DE"     "PORRES"
## 
## [[36]]
## [1] "150136" "SAN"    "MIGUEL"
## 
## [[37]]
## [1] "150137" "SANTA"  "ANITA" 
## 
## [[38]]
## [1] "150138" "SANTA"  "MARIA"  "DEL"    "MAR"   
## 
## [[39]]
## [1] "150139" "SANTA"  "ROSA"  
## 
## [[40]]
## [1] "150140"   "SANTIAGO" "DE"       "SURCO"   
## 
## [[41]]
## [1] "150141"    "SURQUILLO"
## 
## [[42]]
## [1] "150142"   "VILLA"    "EL"       "SALVADOR"
## 
## [[43]]
## [1] "150143"  "VILLA"   "MARIA"   "DEL"     "TRIUNFO"
## 
## [[44]]
## [1] ""
## 
## [[45]]
## [1] ""
## 
## [[46]]
##  [1] "Nota"        "1: El"       "delito"      "contra"      "el"         
##  [6] "patrimonio"  "cultural,"   "se recoge a" "partir"      "del"        
## [11] "a񯠲015."     
## 
## [[47]]
##  [1] "Nota"           "2: La"          "clasificaci󮠤e"  "delitos"       
##  [5] "por"            "espec_xD9A9_co" "y"              "modalidad"     
##  [9] "para"           "los"            "a񯳠2012-2014,"   "corresponde"   
## [13] "a"              "Lima"           "Metropolitana."
## 
## [[48]]
##  [1] "Nota"         "3: Las"       "denuncias"    "de"           "delitos"     
##  [6] "corresponden" "al"           "lugar"        "donde"        "ocurri󠥬"     
## [11] "hecho"        "delictivo."  
## 
## [[49]]
##  [1] "Nota"                "4: La"               "informaci󮠲egistrada"
##  [4] "en"                  "el"                  "2023,"              
##  [7] "corresponde"         "a"                   "enero"              
## [10] "_x0013_"             "agosto."            
## 
## [[50]]
##  [1] "Nota"         "5: Para"      "el"           "periodo"      "2011-2017"   
##  [6] "se"           "utiliz󠬡"      "poblaci󮠤e"    "los"          "Censos"      
## [11] "Nacionales"   "de"           "Poblaci󮠲007," "y"            "del"         
## [16] "2018"         "en"           "adelante"     "se"           "utiliz󠬡"     
## [21] "poblaci󮠤e"    "los"          "Censos"       "Nacionales"   "de"          
## [26] "Poblaci󮠲017."
## 
## [[51]]
##  [1] "Nota"          "6:"            "A"             "partir"       
##  [5] "del"           "a񯠲018"         "comprende las" "denuncias"    
##  [9] "registradas"   "en"            "el"            "Sistema"      
## [13] "de"            "Denuncias"     "Policiales"    "(SIDPOL)."    
## 
## [[52]]
## [1] ""
## 
## [[53]]
##  [1] "1/ Denominaci󮠥stablecida" "mediante"                
##  [3] "Ley"                      "N"                       
##  [5] "31140,"                   "comprende"               
##  [7] "los"                      "43"                      
##  [9] "distritos"                "de"                      
## [11] "la"                       "provincia"               
## [13] "de"                       "Lima."                   
## 
## [[54]]
##  [1] "2/ Denominaci󮠥stablecida" "mediante"                
##  [3] "Ley"                      "N"                       
##  [5] "31140,"                   "constituido"             
##  [7] "por"                      "las"                     
##  [9] "provincias"               "de"                      
## [11] "Barranca,"                "Cajatambo,"              
## [13] "Canta,"                   "Ca񥴥,"                    
## [15] "Huaral,"                  "Huarochir_xDB20_Huaura," 
## [17] "Oy󮠹"                      "Yauyos."                 
## 
## [[55]]
## [1] ""
## 
## [[56]]
##  [1] "Fuente:"        "Instituto"      "Nacional"       "de"            
##  [5] "Estad?ica"      "e"              "Informᴩca"      "(Registro"     
##  [9] "Nacional"       "de"             "Denuncias"      "de"            
## [13] "Delitos"        "y"              "Faltas)"        "-"             
## [17] "Polic?Nacional" "del"            "Per"            "(Sistema"      
## [21] "de"             "Denuncias"      "Policiales)."
DATADENUN$UBI=str_split(string = DATADENUN$V1,
                         pattern = ' ',
                         simplify = T)[,1]

DATADENUN$Distrito=str_split(string = DATADENUN$V1,
                          pattern = ' ',
                          simplify = T)[,2]
DATADENUN$TasaDenun=DATADENUN$V3
DATADENUN <- DATADENUN[, c("UBI", "Distrito", "TasaDenun")]
loqsalgap <- head(DATADENUN, -13)
names(RESIDUOS) <- as.character(RESIDUOS[1, ])
DATARESI <- RESIDUOS[-1, ]
DATARESI <- RESIDUOS[, c("PROVINCIA", "DISTRITO", "QRESIDUOS_NO_DOM")]
DATARESI<- DATARESI[-(1:1), ]
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
DATARESI = filter(DATARESI, grepl("LIMA", PROVINCIA))