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18 changes: 12 additions & 6 deletions Week_27/Week_27.Rmd
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---
title: "Week 27 - US Births"
output: github_document
title: "TidyTuesday 2018 - Week 27 - US Births"
output: html_document
author: "Roberto Preste"
date: "`r Sys.Date()`"
date: "2018-10-03"
editor_options:
chunk_output_type: inline
---

This is my work for week 27 (2018) of the [#TidyTuesday](https://thomasmock.netlify.com/post/tidytuesday-a-weekly-social-data-project-in-r/) project.

A funny dataset for this week's TidyTuesday: how many babies are born on Friday 13^th^ compared to other days?
The [original article](https://fivethirtyeight.com/features/some-people-are-too-superstitious-to-have-a-baby-on-friday-the-13th/) and data are offered by fivethirtyeight ([here](https://github.com/rudeboybert/fivethirtyeight) is their GitHub profile, where all the raw data can be found).

All code and data can be found in my dedicated GitHub repository [MyTidyTuesday](https://github.com/robertopreste/MyTidyTuesday).

___

```{r global_options, echo = FALSE, include = FALSE}
options(width = 120)
```
Expand All @@ -21,9 +30,6 @@ library(RColorBrewer)

___

A funny dataset for this week's TidyTuesday: how many babies are born on Friday 13^th^ compared to other days?
The [original article](https://fivethirtyeight.com/features/some-people-are-too-superstitious-to-have-a-baby-on-friday-the-13th/) and data are offered by fivethirtyeight ([here](https://github.com/rudeboybert/fivethirtyeight) is their GitHub profile, where all the raw data can be found).

We will first load the data into R.

```{r results='hide'}
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Week 27 - US Births
TidyTuesday 2018 - Week 27 - US Births
================
Roberto Preste
2018-10-03

This is my work for week 27 (2018) of the
[\#TidyTuesday](https://thomasmock.netlify.com/post/tidytuesday-a-weekly-social-data-project-in-r/)
project.

A funny dataset for this week’s TidyTuesday: how many babies are born on
Friday 13<sup>th</sup> compared to other days?
The [original
article](https://fivethirtyeight.com/features/some-people-are-too-superstitious-to-have-a-baby-on-friday-the-13th/)
and data are offered by fivethirtyeight
([here](https://github.com/rudeboybert/fivethirtyeight) is their GitHub
profile, where all the raw data can be found).

All code and data can be found in my dedicated GitHub repository
[MyTidyTuesday](https://github.com/robertopreste/MyTidyTuesday).

-----

``` r
library(tidyverse)
library(magrittr)
Expand All @@ -11,10 +28,7 @@ library(skimr)
library(RColorBrewer)
```

------------------------------------------------------------------------

A funny dataset for this week's TidyTuesday: how many babies are born on Friday 13<sup>th</sup> compared to other days?
The [original article](https://fivethirtyeight.com/features/some-people-are-too-superstitious-to-have-a-baby-on-friday-the-13th/) and data are offered by fivethirtyeight ([here](https://github.com/rudeboybert/fivethirtyeight) is their GitHub profile, where all the raw data can be found).
-----

We will first load the data into R.

Expand All @@ -24,11 +38,11 @@ df <- read_csv("data/us_births_2000-2014.csv")

## Parsed with column specification:
## cols(
## year = col_integer(),
## month = col_integer(),
## date_of_month = col_integer(),
## day_of_week = col_integer(),
## births = col_integer()
## year = col_double(),
## month = col_double(),
## date_of_month = col_double(),
## day_of_week = col_double(),
## births = col_double()
## )

``` r
Expand All @@ -37,20 +51,19 @@ head(df)

## # A tibble: 6 x 5
## year month date_of_month day_of_week births
## <int> <int> <int> <int> <int>
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2000 1 1 6 9083
## 2 2000 1 2 7 8006
## 3 2000 1 3 1 11363
## 4 2000 1 4 2 13032
## 5 2000 1 5 3 12558
## 6 2000 1 6 4 12466

------------------------------------------------------------------------
-----

Data Exploration
----------------
## Data Exploration

Let's check for missing values and other issues.
Let’s check for missing values and other issues.

``` r
skim(df)
Expand All @@ -60,16 +73,17 @@ skim(df)
## n obs: 5479
## n variables: 5
##
## ── Variable type:integer ──────────────────────────────────────────────────────────────────────────────────────────
## ── Variable type:numeric ────────────────────────────────────────────────────────────────────────────────────────
## variable missing complete n mean sd p0 p25 p50 p75 p100 hist
## births 0 5479 5479 11350.07 2325.82 5728 8740 12343 13082 16081 ▁▃▂▁▃▇▂▁
## date_of_month 0 5479 5479 15.73 8.8 1 8 16 23 31 ▇▇▇▇▆▇▇▇
## day_of_week 0 5479 5479 4 2 1 2 4 6 7 ▇▇▇▇▁▇▇▇
## month 0 5479 5479 6.52 3.45 1 4 7 10 12 ▇▅▇▃▅▇▅▇
## year 0 5479 5479 2007 4.32 2000 2003 2007 2011 2014 ▇▇▇▇▅▇▇▇

Everything seems to be in order.
Let's add another column, `date`, to obtain the proper date from the `year`, `month` and `date_of_month` features.
Everything seems to be in order.
Let’s add another column, `date`, to obtain the proper date from the
`year`, `month` and `date_of_month` features.

``` r
df %<>%
Expand All @@ -82,7 +96,7 @@ df

## # A tibble: 5,479 x 6
## year month date_of_month day_of_week births date
## <int> <int> <int> <int> <int> <date>
## <dbl> <dbl> <dbl> <dbl> <dbl> <date>
## 1 2000 1 1 6 9083 2000-01-01
## 2 2000 1 2 7 8006 2000-01-02
## 3 2000 1 3 1 11363 2000-01-03
Expand All @@ -93,20 +107,20 @@ df
## 8 2000 1 8 6 8934 2000-01-08
## 9 2000 1 9 7 7949 2000-01-09
## 10 2000 1 10 1 11668 2000-01-10
## # ... with 5,469 more rows
## # … with 5,469 more rows

I will create a set of colors that I'll use during this analysis.
I will create a set of colors that I’ll use during this analysis.

``` r
pastels <- brewer.pal(4, "Pastel1")
```

------------------------------------------------------------------------
-----

Discussion
----------
## Discussion

Now we can have a quick look at the distribution of births over the years.
Now we can have a quick look at the distribution of births over the
years.

``` r
df %>%
Expand All @@ -116,10 +130,11 @@ df %>%
labs(x = "Year", y = "Births", title = "Births distribution over years")
```

![](Week_27_files/figure-markdown_github/unnamed-chunk-8-1.png)
![](Week_27_files/figure-gfm/unnamed-chunk-8-1.png)<!-- -->

The number of births each year seems to be quite constant, with a small increase in 2006-2008.
Let's plot the same distribution over months this time.
The number of births each year seems to be quite constant, with a small
increase in 2006-2008.
Let’s plot the same distribution over months this time.

``` r
df %>%
Expand All @@ -130,10 +145,13 @@ df %>%
labs(x = "Month", y = "Births", title = "Births distribution over months")
```

![](Week_27_files/figure-markdown_github/unnamed-chunk-9-1.png)
![](Week_27_files/figure-gfm/unnamed-chunk-9-1.png)<!-- -->

It looks like most births are occurring in September; this is quite interesting, and my guess is that this may due to couples being able to *"spend more time together"* during Christmas holidays, if you know what I mean...
Lastly, let's view the distribution of births over days of a month.
It looks like most births are occurring in September; this is quite
interesting, and my guess is that this may due to couples being able to
*“spend more time together”* during Christmas holidays, if you know what
I mean…
Lastly, let’s view the distribution of births over days of a month.

``` r
day_colors <- c(rep(pastels[2], 12), pastels[1], rep(pastels[2], 18))
Expand All @@ -144,9 +162,12 @@ df %>%
labs(x = "Day of month", y = "Births", title = "Births distribution over days of the month")
```

![](Week_27_files/figure-markdown_github/unnamed-chunk-10-1.png)
![](Week_27_files/figure-gfm/unnamed-chunk-10-1.png)<!-- -->

And there it is! Each 13<sup>th</sup> day the number of births is a bit lower than the other days; the same is true for the 31<sup>st</sup>, but this may be due to months having only 30 days. Let's explore a bit more by plotting the same per-day distribution splitted by month.
And there it is\! Each 13<sup>th</sup> day the number of births is a bit
lower than the other days; the same is true for the 31<sup>st</sup>, but
this may be due to months having only 30 days. Let’s explore a bit more
by plotting the same per-day distribution splitted by month.

``` r
df %>%
Expand All @@ -158,12 +179,17 @@ df %>%
labs(x = "Day of month", y = "Births", title = "Births distribution over days per each month")
```

![](Week_27_files/figure-markdown_github/unnamed-chunk-11-1.png)
![](Week_27_files/figure-gfm/unnamed-chunk-11-1.png)<!-- -->

Although this is quite an ugly plot, we can see that usually every 13<sup>th</sup> of each month few babies are born. The same occurs with national holydays, and this is obvious from the drop in the number of births around Christmas, or on the 4<sup>th</sup> of July, or during the last few days of November for Thanksgiving.
Although this is quite an ugly plot, we can see that usually every
13<sup>th</sup> of each month few babies are born. The same occurs with
national holydays, and this is obvious from the drop in the number of
births around Christmas, or on the 4<sup>th</sup> of July, or during the
last few days of November for Thanksgiving.

But we haven't still explored the number of births occurring on Friday 13<sup>th</sup>.
Let's first see how birth are distributed over days of the week.
But we haven’t still explored the number of births occurring on Friday
13<sup>th</sup>.
Let’s first see how birth are distributed over days of the week.

``` r
week_colors <- c(rep(pastels[2], 5), rep(pastels[1], 2))
Expand All @@ -175,10 +201,12 @@ df %>%
labs(x = "Day of the week", y = "Births", title = "Births distribution over the week")
```

![](Week_27_files/figure-markdown_github/unnamed-chunk-12-1.png)
![](Week_27_files/figure-gfm/unnamed-chunk-12-1.png)<!-- -->

We can see a strong dicrease in the number of newborns during the weekends, and this is quite expected.
Now let's gather all these information and actually check if Friday 13<sup>th</sup> is really a no-no for delivering babies.
We can see a strong dicrease in the number of newborns during the
weekends, and this is quite expected.
Now let’s gather all these information and actually check if Friday
13<sup>th</sup> is really a no-no for delivering babies.

``` r
df %>%
Expand All @@ -195,41 +223,43 @@ df %>%
theme(legend.position = "bottom")
```

![](Week_27_files/figure-markdown_github/unnamed-chunk-13-1.png)
![](Week_27_files/figure-gfm/unnamed-chunk-13-1.png)<!-- -->

From what we see, there is no actual decrease in the number of births on Friday 13<sup>th</sup>, but rather on the 13<sup>th</sup> of each month, regardless of the day of the week.
From what we see, there is no actual decrease in the number of births on
Friday 13<sup>th</sup>, but rather on the 13<sup>th</sup> of each month,
regardless of the day of the week.

------------------------------------------------------------------------
-----

``` r
sessionInfo()
```

## R version 3.5.1 (2018-07-02)
## R version 3.6.0 (2019-04-26)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS 10.14
## Running under: macOS Mojave 10.14.5
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
## BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] bindrcpp_0.2.2 RColorBrewer_1.1-2 skimr_1.0.3 lubridate_1.7.4 magrittr_1.5 forcats_0.3.0
## [7] stringr_1.3.1 dplyr_0.7.6 purrr_0.2.5 readr_1.1.1 tidyr_0.8.1 tibble_1.4.2
## [13] ggplot2_3.0.0 tidyverse_1.2.1
## [1] RColorBrewer_1.1-2 skimr_1.0.6 lubridate_1.7.4 magrittr_1.5 forcats_0.4.0 stringr_1.4.0
## [7] dplyr_0.8.1 purrr_0.3.2 readr_1.3.1 tidyr_0.8.3 tibble_2.1.1 ggplot2_3.1.1
## [13] tidyverse_1.2.1
##
## loaded via a namespace (and not attached):
## [1] tidyselect_0.2.4 haven_1.1.2 lattice_0.20-35 colorspace_1.3-2 htmltools_0.3.6 yaml_2.2.0
## [7] utf8_1.1.4 rlang_0.2.2 pillar_1.3.0 glue_1.3.0 withr_2.1.2 modelr_0.1.2
## [13] readxl_1.1.0 bindr_0.1.1 plyr_1.8.4 munsell_0.5.0 gtable_0.2.0 cellranger_1.1.0
## [19] rvest_0.3.2 evaluate_0.11 labeling_0.3 knitr_1.20 fansi_0.3.0 broom_0.5.0
## [25] Rcpp_0.12.18 scales_1.0.0 backports_1.1.2 jsonlite_1.5 hms_0.4.2 digest_0.6.17
## [31] stringi_1.2.4 grid_3.5.1 rprojroot_1.3-2 cli_1.0.0 tools_3.5.1 lazyeval_0.2.1
## [37] crayon_1.3.4 pkgconfig_2.0.2 xml2_1.2.0 assertthat_0.2.0 rmarkdown_1.10 httr_1.3.1
## [43] rstudioapi_0.7 R6_2.2.2 nlme_3.1-137 compiler_3.5.1
## [1] tidyselect_0.2.5 xfun_0.7 haven_2.1.0 lattice_0.20-38 colorspace_1.4-1 generics_0.0.2
## [7] vctrs_0.1.0 htmltools_0.3.6 yaml_2.2.0 utf8_1.1.4 rlang_0.3.4 pillar_1.4.1
## [13] glue_1.3.1 withr_2.1.2 modelr_0.1.4 readxl_1.3.1 plyr_1.8.4 munsell_0.5.0
## [19] gtable_0.3.0 cellranger_1.1.0 rvest_0.3.4 evaluate_0.14 labeling_0.3 knitr_1.23
## [25] fansi_0.4.0 broom_0.5.2 Rcpp_1.0.1 scales_1.0.0 backports_1.1.4 jsonlite_1.6
## [31] hms_0.4.2 digest_0.6.19 stringi_1.4.3 grid_3.6.0 cli_1.1.0 tools_3.6.0
## [37] lazyeval_0.2.2 crayon_1.3.4 pkgconfig_2.0.2 zeallot_0.1.0 xml2_1.2.0 assertthat_0.2.1
## [43] rmarkdown_1.13 httr_1.4.0 rstudioapi_0.10 R6_2.4.0 nlme_3.1-139 compiler_3.6.0
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