testing

_freeze/posts/UntitledRMD/execute-results/html.json

@@ -0,0 +1,16 @@
+{
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+    "markdown": "---\ntitle: \"Exploratory Data Analysis\"\nauthor: \"Ning Duan\"\ndate: \"10/26/2022\"\noutput: pdf_document\n---\n\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(readr)\nall_data_guage_labworks <- read_csv(\"/Users/duanning/Downloads/Regression-Modelling/posts/_data/all_data_guage_labworks.csv\")\n```\n\n::: {.cell-output .cell-output-stderr}\n```\nNew names:\nRows: 159 Columns: 29\n── Column specification\n──────────────────────────────────────────────────────── Delimiter: \",\" chr\n(17): Agency_cd, Name, Tz_cd, Ph-Status, Do-Status, Sc-Status, Turb-Stat... dbl\n(12): ...1, Site_no, Datetime, Ph, Do, Sc, Turb_fnu, Wl_elev, Temp_c, Q_...\nℹ Use `spec()` to retrieve the full column specification for this data. ℹ\nSpecify the column types or set `show_col_types = FALSE` to quiet this message.\n• `` -> `...1`\n```\n:::\n\n```{.r .cell-code}\ncolnames(all_data_guage_labworks)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n [1] \"...1\"           \"Agency_cd\"      \"Name\"           \"Site_no\"       \n [5] \"Datetime\"       \"Tz_cd\"          \"Ph\"             \"Ph-Status\"     \n [9] \"Do\"             \"Do-Status\"      \"Sc\"             \"Sc-Status\"     \n[13] \"Turb_fnu\"       \"Turb-Status\"    \"Wl_elev\"        \"Wl_elev-Status\"\n[17] \"Temp_c\"         \"Temp-Status\"    \"Q_cfs\"          \"Q-Status\"      \n[21] \"Stage_ft\"       \"Stage - Status\" \"Precip_in\"      \"Precip-Status\" \n[25] \"Waterbody\"      \"Lcod\"           \"Ecoli_mpn\"      \"Fecal_cfu\"     \n[29] \"Turbidity_ntu\" \n```\n:::\n\n```{.r .cell-code}\nsummary(all_data_guage_labworks)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n      ...1        Agency_cd             Name              Site_no       \n Min.   :  1.0   Length:159         Length:159         Min.   :3451500  \n 1st Qu.: 40.5   Class :character   Class :character   1st Qu.:3451500  \n Median : 80.0   Mode  :character   Mode  :character   Median :3451500  \n Mean   : 80.0                                         Mean   :3451500  \n 3rd Qu.:119.5                                         3rd Qu.:3451500  \n Max.   :159.0                                         Max.   :3451500  \n                                                                        \n    Datetime            Tz_cd                 Ph         Ph-Status        \n Min.   :1.559e+09   Length:159         Min.   :6.400   Length:159        \n 1st Qu.:1.593e+09   Class :character   1st Qu.:6.900   Class :character  \n Median :1.623e+09   Mode  :character   Median :7.000   Mode  :character  \n Mean   :1.616e+09                      Mean   :6.972                     \n 3rd Qu.:1.648e+09                      3rd Qu.:7.100                     \n Max.   :1.663e+09                      Max.   :7.400                     \n                                        NA's   :4                         \n       Do          Do-Status               Sc         Sc-Status        \n Min.   : 6.700   Length:159         Min.   :30.00   Length:159        \n 1st Qu.: 7.700   Class :character   1st Qu.:41.00   Class :character  \n Median : 8.000   Mode  :character   Median :45.00   Mode  :character  \n Mean   : 8.353                      Mean   :44.77                     \n 3rd Qu.: 8.600                      3rd Qu.:48.00                     \n Max.   :12.800                      Max.   :59.00                     \n NA's   :4                           NA's   :4                         \n    Turb_fnu      Turb-Status           Wl_elev     Wl_elev-Status    \n Min.   :  2.80   Length:159         Min.   :1951   Length:159        \n 1st Qu.:  8.55   Class :character   1st Qu.:1952   Class :character  \n Median : 16.35   Mode  :character   Median :1952   Mode  :character  \n Mean   : 28.81                      Mean   :1952                     \n 3rd Qu.: 29.82                      3rd Qu.:1953                     \n Max.   :354.00                      Max.   :1958                     \n NA's   :13                          NA's   :62                       \n     Temp_c      Temp-Status            Q_cfs         Q-Status        \n Min.   : 1.90   Length:159         Min.   :  975   Length:159        \n 1st Qu.:18.00   Class :character   1st Qu.: 1460   Class :character  \n Median :21.00   Mode  :character   Median : 1850   Mode  :character  \n Mean   :19.27                      Mean   : 2521                     \n 3rd Qu.:22.20                      3rd Qu.: 2580                     \n Max.   :24.60                      Max.   :16600                     \n NA's   :2                                                            \n    Stage_ft     Stage - Status       Precip_in        Precip-Status     \n Min.   :1.540   Length:159         Min.   :0.000000   Length:159        \n 1st Qu.:1.900   Class :character   1st Qu.:0.000000   Class :character  \n Median :2.150   Mode  :character   Median :0.000000   Mode  :character  \n Mean   :2.473                      Mean   :0.001258                     \n 3rd Qu.:2.600                      3rd Qu.:0.000000                     \n Max.   :8.410                      Max.   :0.070000                     \n                                                                         \n  Waterbody             Lcod            Ecoli_mpn          Fecal_cfu        \n Length:159         Length:159         Length:159         Length:159        \n Class :character   Class :character   Class :character   Class :character  \n Mode  :character   Mode  :character   Mode  :character   Mode  :character  \n                                                                            \n                                                                            \n                                                                            \n                                                                            \n Turbidity_ntu     \n Length:159        \n Class :character  \n Mode  :character  \n                   \n                   \n                   \n                   \n```\n:::\n\n```{.r .cell-code}\nunique(all_data_guage_labworks$Tz_cd)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"EDT\" \"EST\"\n```\n:::\n\n```{.r .cell-code}\nunique(all_data_guage_labworks$`Ph-Status`)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] NA  \"A\" \"P\"\n```\n:::\n\n```{.r .cell-code}\nunique(all_data_guage_labworks$`Do-Status`)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] NA  \"A\" \"P\"\n```\n:::\n\n```{.r .cell-code}\nunique(all_data_guage_labworks$`Sc-Status`)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] NA  \"A\" \"P\"\n```\n:::\n\n```{.r .cell-code}\nunique(all_data_guage_labworks$`Turb-Status`)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] NA  \"A\" \"P\"\n```\n:::\n\n```{.r .cell-code}\nunique(all_data_guage_labworks$`Wl_elev-Status`)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] NA  \"P\"\n```\n:::\n\n```{.r .cell-code}\nunique(all_data_guage_labworks$`Temp-Status`)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"A\" NA  \"P\"\n```\n:::\n\n```{.r .cell-code}\nunique(all_data_guage_labworks$`Q-Status`)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"A\" \"P\"\n```\n:::\n\n```{.r .cell-code}\nunique(all_data_guage_labworks$`Stage - Status`)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"A\" \"P\"\n```\n:::\n\n```{.r .cell-code}\nunique(all_data_guage_labworks$`Precip-Status`)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"A\" \"P\"\n```\n:::\n\n```{.r .cell-code}\nunique(all_data_guage_labworks$`Waterbody`)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"FBR\"\n```\n:::\n\n```{.r .cell-code}\nunique(all_data_guage_labworks$`Lcod`)\n```\n\n::: {.cell-output .cell-output-stdout}\n```\n[1] \"FRBECOLI2\"\n```\n:::\n:::\n\n\nResponse: \"Ecoli_mpn\" (lab result).\n\nPredictors: \"Ph\" \"Do\" \"Sc\" \"Turb_fnu\" \"Wl_elev\" \"Temp_c\" \"Q_cfs\" \"Stage_ft\" \"Precip_in\"\n\n\n::: {.cell}\n\n```{.r .cell-code}\nlibrary(ggplot2)\n\nggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = as.numeric(all_data_guage_labworks$Ecoli_mpn))) +\n  geom_point()\n```\n\n::: {.cell-output .cell-output-stderr}\n```\nWarning in FUN(X[[i]], ...): NAs introduced by coercion\n\nWarning in FUN(X[[i]], ...): NAs introduced by coercion\n```\n:::\n\n::: {.cell-output .cell-output-stderr}\n```\nWarning: Removed 2 rows containing missing values (geom_point).\n```\n:::\n\n::: {.cell-output-display}\n![](UntitledRMD_files/figure-html/unnamed-chunk-1-1.png){width=672}\n:::\n\n```{.r .cell-code}\nggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Ph)) +\n  geom_point()\n```\n\n::: {.cell-output .cell-output-stderr}\n```\nWarning: Removed 4 rows containing missing values (geom_point).\n```\n:::\n\n::: {.cell-output-display}\n![](UntitledRMD_files/figure-html/unnamed-chunk-1-2.png){width=672}\n:::\n\n```{.r .cell-code}\nggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Do)) +\n  geom_point()\n```\n\n::: {.cell-output .cell-output-stderr}\n```\nWarning: Removed 4 rows containing missing values (geom_point).\n```\n:::\n\n::: {.cell-output-display}\n![](UntitledRMD_files/figure-html/unnamed-chunk-1-3.png){width=672}\n:::\n\n```{.r .cell-code}\nggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Sc)) +\n  geom_point()\n```\n\n::: {.cell-output .cell-output-stderr}\n```\nWarning: Removed 4 rows containing missing values (geom_point).\n```\n:::\n\n::: {.cell-output-display}\n![](UntitledRMD_files/figure-html/unnamed-chunk-1-4.png){width=672}\n:::\n\n```{.r .cell-code}\nggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Turb_fnu)) +\n  geom_point()\n```\n\n::: {.cell-output .cell-output-stderr}\n```\nWarning: Removed 13 rows containing missing values (geom_point).\n```\n:::\n\n::: {.cell-output-display}\n![](UntitledRMD_files/figure-html/unnamed-chunk-1-5.png){width=672}\n:::\n\n```{.r .cell-code}\nggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Wl_elev)) +\n  geom_point()\n```\n\n::: {.cell-output .cell-output-stderr}\n```\nWarning: Removed 62 rows containing missing values (geom_point).\n```\n:::\n\n::: {.cell-output-display}\n![](UntitledRMD_files/figure-html/unnamed-chunk-1-6.png){width=672}\n:::\n\n```{.r .cell-code}\nggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Temp_c)) +\n  geom_point()\n```\n\n::: {.cell-output .cell-output-stderr}\n```\nWarning: Removed 2 rows containing missing values (geom_point).\n```\n:::\n\n::: {.cell-output-display}\n![](UntitledRMD_files/figure-html/unnamed-chunk-1-7.png){width=672}\n:::\n\n```{.r .cell-code}\nggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Q_cfs)) +\n  geom_point()\n```\n\n::: {.cell-output-display}\n![](UntitledRMD_files/figure-html/unnamed-chunk-1-8.png){width=672}\n:::\n\n```{.r .cell-code}\nggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Stage_ft)) +\n  geom_point()\n```\n\n::: {.cell-output-display}\n![](UntitledRMD_files/figure-html/unnamed-chunk-1-9.png){width=672}\n:::\n\n```{.r .cell-code}\nggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Precip_in)) +\n  geom_point()\n```\n\n::: {.cell-output-display}\n![](UntitledRMD_files/figure-html/unnamed-chunk-1-10.png){width=672}\n:::\n:::\n\n::: {.cell}\n\n```{.r .cell-code}\npairs(~ as.numeric(Ecoli_mpn) + Ph + Do+ Sc + Turb_fnu + Wl_elev + Temp_c + Q_cfs + Stage_ft + Precip_in, data = all_data_guage_labworks)\n```\n\n::: {.cell-output .cell-output-stderr}\n```\nWarning in eval(predvars, data, env): NAs introduced by coercion\n```\n:::\n\n::: {.cell-output-display}\n![](UntitledRMD_files/figure-html/unnamed-chunk-2-1.png){width=672}\n:::\n:::\n",
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+}

posts/exploratory_data_analysis.Rmd

@@ -0,0 +1,86 @@
+---
+title: "Exploratory Data Analysis"
+author: "Ning Duan"
+date: "10/26/2022"
+output: pdf_document
+---
+
+```{r setup, include=FALSE}
+knitr::opts_chunk$set(echo = TRUE)
+```
+
+```{r set up workspace}
+library(readr)
+all_data_guage_labworks <- read_csv("/Users/duanning/Downloads/Regression-Modelling/posts/_data/all_data_guage_labworks.csv")
+colnames(all_data_guage_labworks)
+summary(all_data_guage_labworks)
+
+Ecoli = as.numeric(all_data_guage_labworks$Ecoli_mpn)
+
+unique(all_data_guage_labworks$Tz_cd)
+unique(all_data_guage_labworks$`Ph-Status`)
+unique(all_data_guage_labworks$`Do-Status`)
+unique(all_data_guage_labworks$`Sc-Status`)
+unique(all_data_guage_labworks$`Turb-Status`)
+unique(all_data_guage_labworks$`Wl_elev-Status`)
+unique(all_data_guage_labworks$`Temp-Status`)
+unique(all_data_guage_labworks$`Q-Status`)
+unique(all_data_guage_labworks$`Stage - Status`)
+unique(all_data_guage_labworks$`Precip-Status`)
+unique(all_data_guage_labworks$`Waterbody`)
+unique(all_data_guage_labworks$`Lcod`)
+```
+
+Response: "Ecoli_mpn" (lab result).
+
+Predictors: "Ph" "Do" "Sc" "Turb_fnu" "Wl_elev" "Temp_c" "Q_cfs" "Stage_ft" "Precip_in"
+
+```{r}
+library(ggplot2)
+
+ggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = Ecoli)) +
+  geom_point()
+
+ggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Ph)) +
+  geom_point()
+
+ggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Do)) +
+  geom_point()
+
+ggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Sc)) +
+  geom_point()
+
+ggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Turb_fnu)) +
+  geom_point()
+
+ggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Wl_elev)) +
+  geom_point()
+
+ggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Temp_c)) +
+  geom_point()
+
+ggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Q_cfs)) +
+  geom_point()
+
+ggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Stage_ft)) +
+  geom_point()
+
+ggplot(all_data_guage_labworks, aes(x = 1:nrow(all_data_guage_labworks), y = all_data_guage_labworks$Precip_in)) +
+  geom_point()
+```
+
+```{r}
+pairs(~ Ecoli + Ph + Do+ Sc + Turb_fnu + Wl_elev + Temp_c + Q_cfs + Stage_ft + Precip_in, data = all_data_guage_labworks)
+```
+
+```{r}
+m1 = lm(Ecoli ~ Ph + Do+ Sc + Turb_fnu + Wl_elev + Temp_c + Q_cfs + Stage_ft + Precip_in, data = all_data_guage_labworks)
+summary(m1)
+```
+
+A simple linear regression model.
+
+```{r}
+pairs(~ Wl_elev + Q_cfs + Stage_ft, data = all_data_guage_labworks)
+```
+Question: Are Wl_elev, Q_cfs, and Stage_ft transformations of each other?