FEC Previous Cycles.Rmd

---
title: "R Notebook"
output: html_notebook
---


Individual Donations
```{r}

# individual donations header
ind_header <- t((fread("input data/FEC/Individual/indiv_header_file.csv", header=FALSE)))

# individual donations 2012
ind_12 <- read.table("input data/FEC/Individual/indiv12/itcont.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = ind_header[,1]) %>%
            filter(str_sub(toString(TRANSACTION_DT), -4, -1) == "2012") %>%
            select(TRAN_ID, TRANSACTION_DT, TRANSACTION_AMT, CMTE_ID, STATE)
head(ind_12)

# individual donations 2014
ind_14 <- read.table("input data/FEC/Individual/indiv14/itcont.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = ind_header[,1]) %>%
            filter(str_sub(toString(TRANSACTION_DT), -4, -1) == "2014") %>%
            select(TRAN_ID, TRANSACTION_DT, TRANSACTION_AMT, CMTE_ID, STATE)
head(ind_14)

# individual donations 2016
ind_16 <- read.table("input data/FEC/Individual/indiv16/itcont.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = ind_header[,1]) %>%
            filter(str_sub(toString(TRANSACTION_DT), -4, -1) == "2016") %>%
            select(TRAN_ID, TRANSACTION_DT, TRANSACTION_AMT, CMTE_ID, STATE)
head(ind_16)

# individual donations 2018
ind_18 <- read.table("input data/FEC/Individual/indiv18/itcont.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = ind_header[,1]) %>%
            filter(str_sub(toString(TRANSACTION_DT), -4, -1) == "2018") %>%
            select(TRAN_ID, TRANSACTION_DT, TRANSACTION_AMT, CMTE_ID, STATE)
head(ind_18)

# individual donations 2020
ind_20 <- read.table("input data/FEC/Individual/indiv20/itcont.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = ind_header[,1]) %>%
            filter(str_sub(toString(TRANSACTION_DT), -4, -1) == "2020") %>%
            select(TRAN_ID, TRANSACTION_DT, TRANSACTION_AMT, CMTE_ID, STATE)
head(ind_20)

# individual donations 2022
ind_22 <- read.table("input data/FEC/Individual/indiv22/itcont.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = ind_header[,1]) %>%
            filter(str_sub(toString(TRANSACTION_DT), -4, -1) == "2022") %>%
            select(TRAN_ID, TRANSACTION_DT, TRANSACTION_AMT, CMTE_ID, STATE)
head(ind_22)

```


FEC Candidates
```{r}

# candidate header
cn_header <- t((fread("input data/FEC/Candidates/cn_header_file.csv", header=FALSE)))

# candidates 2012
cn_12 <- read.table("input data/FEC/Candidates/cn12.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = cn_header[,1]) %>%
         filter(CAND_ELECTION_YR == 2012 & (CAND_OFFICE == "H" | CAND_OFFICE == "S") & (CAND_PTY_AFFILIATION == "REP" | CAND_PTY_AFFILIATION == "DEM")) %>%
         select(CAND_ID, CAND_NAME, CAND_PTY_AFFILIATION, CAND_ELECTION_YR, CAND_OFFICE, CAND_OFFICE_ST, CAND_OFFICE_DISTRICT, CAND_PCC)
head(cn_12)
write.csv(cn_12, "output data/FEC Candidates/cn_12.csv")

# candidates 2014
cn_14 <- read.table("input data/FEC/Candidates/cn14.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = cn_header[,1]) %>%
         filter(CAND_ELECTION_YR == 2014 & (CAND_OFFICE == "H" | CAND_OFFICE == "S") & (CAND_PTY_AFFILIATION == "REP" | CAND_PTY_AFFILIATION == "DEM")) %>%
         select(CAND_ID, CAND_NAME, CAND_PTY_AFFILIATION, CAND_ELECTION_YR, CAND_OFFICE, CAND_OFFICE_ST, CAND_OFFICE_DISTRICT, CAND_PCC)
head(cn_14)
write.csv(cn_14, "output data/FEC Candidates/cn_14.csv")

# candidates 2016
cn_16 <- read.table("input data/FEC/Candidates/cn16.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = cn_header[,1]) %>%
         filter(CAND_ELECTION_YR == 2016 & (CAND_OFFICE == "H" | CAND_OFFICE == "S") & (CAND_PTY_AFFILIATION == "REP" | CAND_PTY_AFFILIATION == "DEM")) %>%
         select(CAND_ID, CAND_NAME, CAND_PTY_AFFILIATION, CAND_ELECTION_YR, CAND_OFFICE, CAND_OFFICE_ST, CAND_OFFICE_DISTRICT, CAND_PCC)
head(cn_16)
write.csv(cn_16, "output data/FEC Candidates/cn_16.csv")

# candidates 2018
cn_18 <- read.table("input data/FEC/Candidates/cn18.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = cn_header[,1]) %>%
         filter(CAND_ELECTION_YR == 2018 & (CAND_OFFICE == "H" | CAND_OFFICE == "S") & (CAND_PTY_AFFILIATION == "REP" | CAND_PTY_AFFILIATION == "DEM")) %>%
         select(CAND_ID, CAND_NAME, CAND_PTY_AFFILIATION, CAND_ELECTION_YR, CAND_OFFICE, CAND_OFFICE_ST, CAND_OFFICE_DISTRICT, CAND_PCC)
head(cn_18)
write.csv(cn_18, "output data/FEC Candidates/cn_18.csv")

# candidates 2020
cn_20 <- read.table("input data/FEC/Candidates/cn20.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = cn_header[,1]) %>%
         filter(CAND_ELECTION_YR == 2020 & (CAND_OFFICE == "H" | CAND_OFFICE == "S") & (CAND_PTY_AFFILIATION == "REP" | CAND_PTY_AFFILIATION == "DEM")) %>%
         select(CAND_ID, CAND_NAME, CAND_PTY_AFFILIATION, CAND_ELECTION_YR, CAND_OFFICE, CAND_OFFICE_ST, CAND_OFFICE_DISTRICT, CAND_PCC)
head(cn_20)
write.csv(cn_20, "output data/FEC Candidates/cn_20.csv")

# candidates 2022
cn_22 <- read.table("input data/FEC/Candidates/cn22.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = cn_header[,1]) %>%
         filter(CAND_ELECTION_YR == 2022 & (CAND_OFFICE == "H" | CAND_OFFICE == "S") & (CAND_PTY_AFFILIATION == "REP" | CAND_PTY_AFFILIATION == "DEM")) %>%
         select(CAND_ID, CAND_NAME, CAND_PTY_AFFILIATION, CAND_ELECTION_YR, CAND_OFFICE, CAND_OFFICE_ST, CAND_OFFICE_DISTRICT, CAND_PCC)
head(cn_22)
write.csv(cn_22, "output data/FEC Candidates/cn_22.csv")

```


FEC Candidate-Committee Linkage
```{r}

# candidate-committee linkage header
ccl_header <- t((fread("input data/FEC/Candidate-Committee Linkage/ccl_header_file.csv", header=FALSE)))

# candidate-committee linkage 2012
ccl_12 <- read.table("input data/FEC/Candidate-Committee Linkage/ccl12.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = ccl_header[,1]) %>%                 filter(CAND_ELECTION_YR == 2012) %>%
          select(CAND_ID, CAND_ELECTION_YR, CMTE_ID, LINKAGE_ID)
head(ccl_12) 
write.csv(ccl_12, "output data/FEC Candidate-Committee/ccl_12.csv")

# candidate-committee linkage 2014
ccl_14 <- read.table("input data/FEC/Candidate-Committee Linkage/ccl14.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = ccl_header[,1]) %>%
          filter(CAND_ELECTION_YR == 2014) %>%
          select(CAND_ID, CAND_ELECTION_YR, CMTE_ID, LINKAGE_ID)
head(ccl_14)
write.csv(ccl_14, "output data/FEC Candidate-Committee/ccl_14.csv")

# candidate-committee linkage 2016
ccl_16 <- read.table("input data/FEC/Candidate-Committee Linkage/ccl16.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = ccl_header[,1]) %>%
          filter(CAND_ELECTION_YR == 2016) %>%
          select(CAND_ID, CAND_ELECTION_YR, CMTE_ID, LINKAGE_ID)
head(ccl_16)
write.csv(ccl_16, "output data/FEC Candidate-Committee/ccl_16.csv")

# candidate-committee linkage 2018
ccl_18 <- read.table("input data/FEC/Candidate-Committee Linkage/ccl18.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = ccl_header[,1]) %>%
          filter(CAND_ELECTION_YR == 2018) %>%
          select(CAND_ID, CAND_ELECTION_YR, CMTE_ID, LINKAGE_ID)
head(ccl_18)
write.csv(ccl_18, "output data/FEC Candidate-Committee/ccl_18.csv")

# candidate-committee linkage 2020
ccl_20 <- read.table("input data/FEC/Candidate-Committee Linkage/ccl20.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = ccl_header[,1]) %>%
          filter(CAND_ELECTION_YR == 2020) %>%
          select(CAND_ID, CAND_ELECTION_YR, CMTE_ID, LINKAGE_ID)
head(ccl_20)
write.csv(ccl_20, "output data/FEC Candidate-Committee/ccl_20.csv")

# candidate-committee linkage 2022
ccl_22 <- read.table("input data/FEC/Candidate-Committee Linkage/ccl22.txt", header=FALSE, sep = '|', fill = TRUE, quote = "", col.names = ccl_header[,1]) %>%
          filter(CAND_ELECTION_YR == 2022) %>%
          select(CAND_ID, CAND_ELECTION_YR, CMTE_ID, LINKAGE_ID)
head(ccl_22)
write.csv(ccl_22, "output data/FEC Candidate-Committee/ccl_22.csv")

```


Join FEC Data
```{r}

# 2012 fec data
fec_12 <- ind_12 %>% 
              inner_join(ccl_12, by = c("CMTE_ID")) %>%
              inner_join(cn_12, by = c("CAND_ID"))
head(fec_12)
write.csv(fec_12, "output data/FEC Joined/fec_12.csv")

# 2014 fec data
fec_14 <- ind_14 %>% 
              inner_join(ccl_14, by = c("CMTE_ID")) %>%
              inner_join(cn_14, by = c("CAND_ID"))
head(fec_14)
write.csv(fec_14, "output data/FEC Joined/fec_14.csv")

# 2016 fec data
fec_16 <- ind_16 %>% 
              inner_join(ccl_16, by = c("CMTE_ID")) %>%
              inner_join(cn_16, by = c("CAND_ID"))
head(fec_16)
write.csv(fec_16, "output data/FEC Joined/fec_16.csv")

# 2018 fec data
fec_18 <- ind_18 %>% 
              inner_join(ccl_18, by = c("CMTE_ID")) %>%
              inner_join(cn_18, by = c("CAND_ID"))
head(fec_18)
write.csv(fec_18, "output data/FEC Joined/fec_18.csv")

# 2020 fec data
fec_20 <- ind_20 %>% 
              inner_join(ccl_20, by = c("CMTE_ID")) %>%
              inner_join(cn_20, by = c("CAND_ID"))
head(fec_20)
write.csv(fec_20, "output data/FEC Joined/fec_20.csv")

# 2022 fec data
fec_22 <- ind_22 %>% 
              inner_join(ccl_22, by = c("CMTE_ID")) %>%
              inner_join(cn_22, by = c("CAND_ID"))
head(fec_22)
write.csv(fec_22, "output data/FEC Joined/fec_22.csv")

```