The Tidyverse

---

## The Tidyverse

### Applications of Data Science - Class 1

### Giora Simchoni

#### `gsimchoni@gmail.com and add #dsapps in subject`

### Stat. and OR Department, TAU
### 2019-12-12

---

<div class="my-footer">
  <span>
    <a href="https://dsapps-2020.github.io/Class_Slides/" target="_blank">Applications of Data Science
    </a>
  </span>
</div>

---

# I don't need to know about wrangling data, I get by.

---

# So, what's wrong with Excel?

(MS Excel is one amazing software. But it lacks:)

- Structure (or rather, structure is up to the user)
- Types to variables
- Automization (you could learn VBA Excel, but the horror)
- Reproducibility
- Open Source
- Extensibility
- Speed and Scale
- Modeling (there *is* a t-test, but the horror)

[MS Excel might be the most dangerous software on the planet](https://www.forbes.com/sites/timworstall/2013/02/13/microsofts-excel-might-be-the-most-dangerous-software-on-the-planet/#667084f5633d) (Tim Worstall, Forbes)

---

# So, what's wrong with base R?

(Base R is one amazing software. But it lacks:)

- Consistency:
  - Function names
  - Function arguments names
  - Function arguments order
  - Function return types (sometimes the same function!)
- Meaningful errors and warnings
- Good choices of default values to arguments
- Speed
- Good and easy visualizations
- One other thing

---

### (In) Consistency - Example 1: Strings

```r
# split a string by pattern: strsplit(string, pattern)
strsplit("Who dis?", " ")
```

```
## [[1]]
## [1] "Who"  "dis?"
```

```r
# find if a pattern exists in a string: grepl(pattern, string)
grepl("di", "Who dis?")
```

```
## [1] TRUE
```

```r
# substitute a pattern in a string: sub(pattern, replace, string)
sub("di", "thi", "Who dis?")
```

```
## [1] "Who this?"
```

```r
# length of a string: nchar(string); length of object: length(obj)
c(nchar("Who dis?"), length("Who dis?"))
```

```
## [1] 8 1
```
]

---

### (In) Consistency - Example 2: Models

```r
n <- 10000
x1 <- runif(n)
x2 <- runif(n)
t <- 1 + 2 * x1 + 3 * x2
y <- rbinom(n, 1, 1 / (1 + exp(-t)))
```

```r
glm(y ~ x1 + x2, family = "binomial")
```

```r
glmnet(as.matrix(cbind(x1, x2)), as.factor(y), family = "binomial")
```

```r
randomForest(as.factor(y) ~ x1 + x2)
```

```r
gbm(y ~ x1 + x2, data = data.frame(x1 = x1, x2 = x2, y = y))
```

😱

---

### (Un) Meaningful Errors - Example

```r
df <- data.frame(Education = 1:5, Ethnicity = c(2, 4, 5, 2, 1))
table(df$Eduction, df$Ethnicity)
```

<pre style="color: red;"><code>## Error in table(df$Eduction, df$Ethnicity): all arguments must have the same
length
</code></pre>

---

### (Bad) Default Values - Example

![](images/bad_args_table.png)

```r
df <- read.csv("../data/bad_args_test.csv")
df$col3
```

```
## [1] a b c d
## Levels: a b c d
```

```r
df <- read.csv("../data/bad_args_test.csv", stringsAsFactors = FALSE)
df$col3
```

```
## [1] "a" "b" "c" "d"
```

---

### (No) Speed - Example

```r
file_path <- "../data/mediocre_file.csv"
df <- read.csv(file_path)
dim(df)
```

```
## [1] 9180   14
```

```r
library(microbenchmark)

microbenchmark(
  read_base = read.csv(file_path),
  read_tidy = read_csv(file_path, col_types = cols()),
  read_dt = data.table::fread(file_path),
  times = 10)
```

```
## Unit: milliseconds
##       expr        min       lq      mean     median       uq      max
##  read_base 263.938201 265.3144 267.12326 267.015151 268.4959 271.9319
##  read_tidy  18.726101  19.2148  24.95933  19.589951  22.2064  63.7732
##    read_dt   8.751801   8.8653  14.22467   9.493901  10.9003  55.6528
##  neval
##     10
##     10
##     10
```

---
class: section-slide

# Detour: The OKCupid Dataset

---

## The OKCupid Dataset

- ~60K active OKCupid users scraped on June 2012
- 35K Male, 25K Female (less awareness for non-binary back then)
- Answers to questions like:
  - Body Type
  - Diet
  - Substance Abuse
  - Education
  - Do you like pets?
  - Open questions, e.g. "On a typical Friday night I am..."
  - And the more boring demographic details like age, height, location, sign, religion etc.
- See [here](https://github.com/rudeboybert/JSE_OkCupid/blob/master/okcupid_codebook.txt) for the full codebook

---
class: section-slide

# End of Detour

---

### (Not) Good Vizualizations - Example

```r
okcupid <- read_csv("../data/okcupid.csv.zip", col_types = cols())
okcupid$income[okcupid$income == -1] <- NA
okcupid$height_cm <- okcupid$height * 2.54
```

```r
plot(okcupid$height_cm, log10(okcupid$income + 1),
     col = c("red", "green")[as.factor(okcupid$sex)])
```

<img src="images/Viz-Base-1.png" width="40%" />
]

---

```r
ggplot(okcupid, aes(height_cm, log10(income + 1), color = sex)) +
  geom_point()
```

<pre style="color: red;"><code>## Warning: Removed 48442 rows containing missing values (geom_point).
</code></pre><img src="images/Viz-Tidy-1.png" width="50%" />

---

## One other thing

Manager: "Give me the average income of women respondents above age 30 grouped by sexual orientation!"

You:

```r
mean_bi <- mean(okcupid$income[okcupid$sex == "f" & okcupid$age > 30 & okcupid$orientation == "bisexual"], na.rm = TRUE)
mean_gay <- mean(okcupid$income[okcupid$sex == "f" & okcupid$age > 30 & okcupid$orientation == "gay"], na.rm = TRUE)
mean_straight <- mean(okcupid$income[okcupid$sex == "f" & okcupid$age > 30 & okcupid$orientation == "straight"], na.rm = TRUE)

data.frame(orientation = c("bisexual", "gay", "straight"),
           income_mean = c(mean_bi, mean_gay, mean_straight))
```

```
##   orientation income_mean
## 1    bisexual   133421.05
## 2         gay    86489.36
## 3    straight    85219.74
```

---

Or the slightly better you:

```r
mean_income_function <- function(orientation) {
  mean(okcupid$income[okcupid$sex == "f" & okcupid$age > 30 & okcupid$orientation == orientation], na.rm = TRUE)
}

mean_bi <- mean_income_function("bisexual")
mean_gay <- mean_income_function("gay")
mean_straight <- mean_income_function("straight")

data.frame(orientation = c("bisexual", "gay", "straight"),
           income_mean = c(mean_bi, mean_gay, mean_straight))
```

```
##   orientation income_mean
## 1    bisexual   133421.05
## 2         gay    86489.36
## 3    straight    85219.74
```

---

Or the even better you:

```r
orientations <- c("bisexual", "gay", "straight")
income_means <- numeric(3)

for (i in seq_along(orientations)) {
  income_means[i] <- mean_income_function(orientations[i])
}

data.frame(orientation = orientations, income_mean = income_means)
```

```
##   orientation income_mean
## 1    bisexual   133421.05
## 2         gay    86489.36
## 3    straight    85219.74
```

---

Or the best you:

```r
okcupid_females_over30 <- with(okcupid, okcupid[sex == "f" & age > 30, ])
aggregate(okcupid_females_over30$income,
          by = list(orientation = okcupid_females_over30$orientation),
          FUN = mean, na.rm = TRUE)
```

```
##   orientation         x
## 1    bisexual 133421.05
## 2         gay  86489.36
## 3    straight  85219.74
```

<br>

Manager: "What? Why would bisexual women have a higher income than straight or gay women? Could you add the median, trimmed mean, standard error and n?"

You: 😱

---
class: section-slide

# The Tidyverse

---

## What *is* The Tidyverse?

> The [tidyverse](https://www.tidyverse.org/) is an opinionated collection of R packages designed for data science. All packages share an underlying design philosophy, grammar, and data structures.

- `tibble`: the `data.frame` re-imagined
- `readr`: importing/exporting (mostly rectangular) data for humans
- `dplyr` + `tidyr`: a grammar of data manipulation
- `purrr`: functional programming in R
- `stringr`: string manipulation
- `ggplot2`: a grammar of graphics

---

The above can all be installed and loaded under the `tidyverse` package:

```r
library(tidyverse)
```

Many more:
- `lubridate`: manipulating dates
- `modelr`, `recipes`, `rsample`, `infer`: tidy modeling/statistics
- `rvest`: web scraping
- `tidytext`: tidy text analysis (life saver)
- `tidygraph` + `ggraph`: manipulating and plotting networks
- `glue`: print like a boss
- countless `gg` extensions (`ggmosaic`, `ggbeeswarm`, `gganimate`, `ggridges` etc.)

---

# What's so great about the Tidyverse?

- Tidy Data
- Consistentcy (in function names, args, return types, documentation)
- The Pipe
- Speed (C++ under the hood)
- `ggplot2`
- The Community

---

## Tidy Data

- Each variable must have its own column.
- Each observation must have its own row.
- Each value must have its own cell.

<br>

---

### Which one of these datasets is tidy? (I)

```r
table1
```

```
## # A tibble: 315 x 4
##    religion      yob n_straight n_total
##    <chr>       <dbl>      <dbl>   <dbl>
##  1 atheist      1950         26      29
##  2 buddhist     1950          6       6
##  3 christian    1950         28      32
##  4 hindu        1950          0       0
##  5 jewish       1950         21      24
##  6 muslim       1950          0       0
##  7 unspecified  1950         71      76
##  8 atheist      1951         31      33
##  9 buddhist     1951         11      11
## 10 christian    1951         23      24
## # ... with 305 more rows
```

---

### Which one of these datasets is tidy? (II)

```r
table2
```

```
## # A tibble: 630 x 4
##    religion    yob type         n
##    <chr>     <dbl> <chr>    <dbl>
##  1 atheist    1950 straight    26
##  2 atheist    1950 total       29
##  3 buddhist   1950 straight     6
##  4 buddhist   1950 total        6
##  5 christian  1950 straight    28
##  6 christian  1950 total       32
##  7 hindu      1950 straight     0
##  8 hindu      1950 total        0
##  9 jewish     1950 straight    21
## 10 jewish     1950 total       24
## # ... with 620 more rows
```

---

### Which one of these datasets is tidy? (III)

```r
table3
```

```
## # A tibble: 315 x 3
##    religion      yob pct_straight
##    <chr>       <dbl> <chr>       
##  1 atheist      1950 26/29       
##  2 buddhist     1950 6/6         
##  3 christian    1950 28/32       
##  4 hindu        1950 0/0         
##  5 jewish       1950 21/24       
##  6 muslim       1950 0/0         
##  7 unspecified  1950 71/76       
##  8 atheist      1951 31/33       
##  9 buddhist     1951 11/11       
## 10 christian    1951 23/24       
## # ... with 305 more rows
```

---

### Which one of these datasets is tidy? (IV)

```r
table4
```

```
## # A tibble: 7 x 91
##   religion n_total_1950 n_total_1951 n_total_1952 n_total_1953 n_total_1954
##   <chr>           <dbl>        <dbl>        <dbl>        <dbl>        <dbl>
## 1 atheist            29           33           34           37           40
## 2 buddhist            6           11           14           16           11
## 3 christi~           32           24           37           47           37
## 4 hindu               0            0            0            1            1
## 5 jewish             24           29           27           23           25
## 6 muslim              0            0            0            0            0
## 7 unspeci~           76           79           83           97           83
## # ... with 85 more variables: n_total_1955 <dbl>, n_total_1956 <dbl>,
## #   n_total_1957 <dbl>, n_total_1958 <dbl>, n_total_1959 <dbl>,
## #   n_total_1960 <dbl>, n_total_1961 <dbl>, n_total_1962 <dbl>,
## #   n_total_1963 <dbl>, n_total_1964 <dbl>, n_total_1965 <dbl>,
## #   n_total_1966 <dbl>, n_total_1967 <dbl>, n_total_1968 <dbl>,
## #   n_total_1969 <dbl>, n_total_1970 <dbl>, n_total_1971 <dbl>,
## #   n_total_1972 <dbl>, n_total_1973 <dbl>, n_total_1974 <dbl>,
## #   n_total_1975 <dbl>, n_total_1976 <dbl>, n_total_1977 <dbl>,
## #   n_total_1978 <dbl>, n_total_1979 <dbl>, n_total_1980 <dbl>,
## #   n_total_1981 <dbl>, n_total_1982 <dbl>, n_total_1983 <dbl>,
## #   n_total_1984 <dbl>, n_total_1985 <dbl>, n_total_1986 <dbl>,
## #   n_total_1987 <dbl>, n_total_1988 <dbl>, n_total_1989 <dbl>,
## #   n_total_1990 <dbl>, n_total_1991 <dbl>, n_total_1992 <dbl>,
## #   n_total_1993 <dbl>, n_total_1994 <dbl>, n_straight_1950 <dbl>,
## #   n_straight_1951 <dbl>, n_straight_1952 <dbl>, n_straight_1953 <dbl>,
## #   n_straight_1954 <dbl>, n_straight_1955 <dbl>, n_straight_1956 <dbl>,
## #   n_straight_1957 <dbl>, n_straight_1958 <dbl>, n_straight_1959 <dbl>,
## #   n_straight_1960 <dbl>, n_straight_1961 <dbl>, n_straight_1962 <dbl>,
## #   n_straight_1963 <dbl>, n_straight_1964 <dbl>, n_straight_1965 <dbl>,
## #   n_straight_1966 <dbl>, n_straight_1967 <dbl>, n_straight_1968 <dbl>,
## #   n_straight_1969 <dbl>, n_straight_1970 <dbl>, n_straight_1971 <dbl>,
## #   n_straight_1972 <dbl>, n_straight_1973 <dbl>, n_straight_1974 <dbl>,
## #   n_straight_1975 <dbl>, n_straight_1976 <dbl>, n_straight_1977 <dbl>,
## #   n_straight_1978 <dbl>, n_straight_1979 <dbl>, n_straight_1980 <dbl>,
## #   n_straight_1981 <dbl>, n_straight_1982 <dbl>, n_straight_1983 <dbl>,
## #   n_straight_1984 <dbl>, n_straight_1985 <dbl>, n_straight_1986 <dbl>,
## #   n_straight_1987 <dbl>, n_straight_1988 <dbl>, n_straight_1989 <dbl>,
## #   n_straight_1990 <dbl>, n_straight_1991 <dbl>, n_straight_1992 <dbl>,
## #   n_straight_1993 <dbl>, n_straight_1994 <dbl>
```

---

### Why Tidy?

> Happy families are all alike; every unhappy family is unhappy in its own way. (Leo Tolstoy)

<br>

> It allows R’s vectorised nature to shine. (Hadley Wickham)

---

### A Tidy dataset will be much easier to transform

```r
table1$pct_straight = table1$n_straight / table1$n_total
table1
```

```
## # A tibble: 315 x 5
##    religion      yob n_straight n_total pct_straight
##    <chr>       <dbl>      <dbl>   <dbl>        <dbl>
##  1 atheist      1950         26      29        0.897
##  2 buddhist     1950          6       6        1    
##  3 christian    1950         28      32        0.875
##  4 hindu        1950          0       0      NaN    
##  5 jewish       1950         21      24        0.875
##  6 muslim       1950          0       0      NaN    
##  7 unspecified  1950         71      76        0.934
##  8 atheist      1951         31      33        0.939
##  9 buddhist     1951         11      11        1    
## 10 christian    1951         23      24        0.958
## # ... with 305 more rows
```

---

### A Tidy dataset will be much easier to plot

```r
ggplot(table1, aes(x = yob, y = pct_straight, color = religion)) +
  geom_smooth(method = "loess", se = FALSE)
```

---
class: section-slide

# Detour: The `tibble`

---

### The `tibble`: the `data.frame` re-imagined

- Prints nicer:

```r
tib1 <- tibble(day = lubridate::today() + runif(1e3) * 30,
               type = sample(letters, 1e3, replace = TRUE),
               quantity = sample(seq(0, 100, 10), 1e3, replace = TRUE))
tib1
```

```
## # A tibble: 1,000 x 3
##    day        type  quantity
##    <date>     <chr>    <dbl>
##  1 2020-01-02 p           40
##  2 2019-12-29 s           90
##  3 2019-12-25 o          100
##  4 2019-12-13 r           40
##  5 2019-12-29 k           10
##  6 2020-01-09 w          100
##  7 2020-01-07 r           70
##  8 2020-01-02 b          100
##  9 2020-01-05 s           50
## 10 2020-01-07 o           10
## # ... with 990 more rows
```

---

```r
df1 <- data.frame(day = lubridate::today() + runif(1e3) * 30,
                  type = sample(letters, 1e3, replace = TRUE),
                  quantity = sample(seq(0, 100, 10), 1e3, replace = TRUE))
df1
```

```
##             day type quantity
## 1    2019-12-13    l       10
## 2    2019-12-24    p       40
## 3    2020-01-05    y       50
## 4    2019-12-18    z       10
## 5    2020-01-03    v       90
## 6    2019-12-26    h       50
## 7    2019-12-27    z       80
## 8    2019-12-13    k       90
## 9    2019-12-31    d       40
## 10   2020-01-08    w       30
## 11   2020-01-08    v      100
## 12   2019-12-13    r       90
## 13   2019-12-14    a       70
## 14   2019-12-24    m       80
## 15   2019-12-30    k       70
## 16   2019-12-15    i       20
## 17   2019-12-22    u       90
## 18   2019-12-17    f       40
## 19   2019-12-17    x      100
## 20   2019-12-29    t       10
## 21   2020-01-10    h       70
## 22   2019-12-24    t       10
## 23   2020-01-01    n        0
## 24   2020-01-05    f       90
## 25   2019-12-19    w       20
## 26   2019-12-21    n       50
## 27   2020-01-09    s       80
## 28   2019-12-21    g       80
## 29   2019-12-31    c       10
## 30   2020-01-08    t      100
## 31   2019-12-30    p        0
## 32   2019-12-24    d       50
## 33   2019-12-21    x       30
## 34   2019-12-25    s       20
## 35   2020-01-08    o       60
## 36   2020-01-07    m      100
## 37   2019-12-26    r       80
## 38   2019-12-24    i       20
## 39   2019-12-18    e       20
## 40   2020-01-06    y       60
## 41   2019-12-30    v       80
## 42   2019-12-23    k       50
## 43   2019-12-29    k       80
## 44   2019-12-29    t      100
## 45   2020-01-06    s      100
## 46   2019-12-22    j       20
## 47   2020-01-01    w       10
## 48   2019-12-15    c       20
## 49   2019-12-18    d       50
## 50   2019-12-25    q       80
## 51   2019-12-28    y       50
## 52   2019-12-21    x       30
## 53   2019-12-29    w       80
## 54   2019-12-25    n       30
## 55   2019-12-22    m       40
## 56   2020-01-05    k       10
## 57   2019-12-14    z        0
## 58   2020-01-09    h       50
## 59   2019-12-30    f        0
## 60   2020-01-10    c       10
## 61   2019-12-31    u       40
## 62   2019-12-21    i       40
## 63   2019-12-21    u       50
## 64   2019-12-15    q       50
## 65   2020-01-05    q       10
## 66   2020-01-02    i        0
## 67   2019-12-26    r       90
## 68   2020-01-09    b        0
## 69   2019-12-28    q       90
## 70   2019-12-18    h       30
## 71   2019-12-23    q       60
## 72   2020-01-06    d       60
## 73   2019-12-17    d       20
## 74   2020-01-09    q       40
## 75   2019-12-29    c       20
## 76   2020-01-04    t       20
## 77   2020-01-08    v       20
## 78   2019-12-15    o       30
## 79   2019-12-31    u       80
## 80   2019-12-23    i       20
## 81   2019-12-15    m       30
## 82   2020-01-01    n       20
## 83   2019-12-25    b       10
## 84   2020-01-09    j       90
## 85   2019-12-25    h       90
## 86   2019-12-14    d       80
## 87   2019-12-25    w       10
## 88   2019-12-21    p       90
## 89   2019-12-15    c       70
## 90   2019-12-12    a       60
## 91   2019-12-31    u       60
## 92   2019-12-15    b        0
## 93   2019-12-21    k        0
## 94   2019-12-16    s      100
## 95   2020-01-02    v       40
## 96   2019-12-23    a       90
## 97   2020-01-09    x       60
## 98   2019-12-27    n        0
## 99   2019-12-31    d      100
## 100  2019-12-23    u       80
## 101  2019-12-25    t        0
## 102  2019-12-22    g       70
## 103  2019-12-12    x      100
## 104  2020-01-06    n      100
## 105  2019-12-20    y       10
## 106  2019-12-25    f      100
## 107  2019-12-24    n      100
## 108  2020-01-01    u       70
## 109  2020-01-01    z       30
## 110  2019-12-15    y       60
## 111  2020-01-01    c       60
## 112  2020-01-01    y       60
## 113  2020-01-09    i       30
## 114  2019-12-18    p       40
## 115  2020-01-05    h       90
## 116  2019-12-26    r       20
## 117  2019-12-12    q       40
## 118  2019-12-30    e      100
## 119  2019-12-22    e       30
## 120  2020-01-10    h       50
## 121  2019-12-24    z       60
## 122  2019-12-28    a       70
## 123  2020-01-02    m       80
## 124  2019-12-28    k       80
## 125  2019-12-24    s       80
## 126  2019-12-25    a      100
## 127  2020-01-02    c       20
## 128  2020-01-06    z       70
## 129  2020-01-06    g       10
## 130  2020-01-03    l      100
## 131  2019-12-26    w       20
## 132  2019-12-24    t       20
## 133  2019-12-21    p       60
## 134  2020-01-10    p       30
## 135  2019-12-12    m       40
## 136  2019-12-16    q       90
## 137  2019-12-20    o       20
## 138  2019-12-21    r       80
## 139  2019-12-12    v       70
## 140  2019-12-18    r       10
## 141  2019-12-24    f       40
## 142  2019-12-18    a        0
## 143  2019-12-13    w       80
## 144  2019-12-21    l       50
## 145  2019-12-27    l       10
## 146  2019-12-24    y       80
## 147  2019-12-13    i       70
## 148  2019-12-30    a       30
## 149  2019-12-12    l       20
## 150  2019-12-28    t       50
## 151  2019-12-12    j       40
## 152  2019-12-17    t       50
## 153  2019-12-22    t      100
## 154  2019-12-29    b       60
## 155  2020-01-07    q        0
## 156  2019-12-28    z       80
## 157  2020-01-10    h       70
## 158  2020-01-10    u       10
## 159  2019-12-18    n       50
## 160  2019-12-26    s       70
## 161  2019-12-22    g       90
## 162  2020-01-03    f       60
## 163  2019-12-28    m       10
## 164  2020-01-01    w       20
## 165  2019-12-14    a      100
## 166  2019-12-28    v      100
## 167  2020-01-03    j       60
## 168  2020-01-03    o       70
## 169  2019-12-30    y       70
## 170  2019-12-28    r       40
## 171  2019-12-26    u       70
## 172  2019-12-19    k       40
## 173  2019-12-19    b       10
## 174  2020-01-07    m       40
## 175  2019-12-16    e       30
## 176  2019-12-15    d       40
## 177  2019-12-19    a       30
## 178  2020-01-03    p       90
## 179  2019-12-16    r       70
## 180  2019-12-24    z        0
## 181  2020-01-10    l       20
## 182  2019-12-15    a       80
## 183  2019-12-17    u       30
## 184  2020-01-07    b       90
## 185  2019-12-25    y       90
## 186  2020-01-07    v       50
## 187  2019-12-21    n       30
## 188  2019-12-29    n       10
## 189  2019-12-27    p       80
## 190  2020-01-07    e       40
## 191  2019-12-16    u       10
## 192  2020-01-04    d      100
## 193  2019-12-21    a       90
## 194  2020-01-10    a       10
## 195  2020-01-04    p       20
## 196  2019-12-12    k       70
## 197  2019-12-19    v       40
## 198  2019-12-16    g      100
## 199  2019-12-25    j       70
## 200  2019-12-26    u       50
## 201  2019-12-14    v       30
## 202  2020-01-03    i       10
## 203  2019-12-12    u       30
## 204  2019-12-18    k       70
## 205  2019-12-14    e        0
## 206  2019-12-30    x       10
## 207  2019-12-25    v       90
## 208  2020-01-08    r       20
## 209  2020-01-04    o       70
## 210  2020-01-05    f       20
## 211  2019-12-18    s       10
## 212  2020-01-02    e       60
## 213  2019-12-26    f       10
## 214  2019-12-14    i       50
## 215  2020-01-09    a       70
## 216  2019-12-16    x       40
## 217  2019-12-23    t       80
## 218  2019-12-21    j       10
## 219  2020-01-03    e       50
## 220  2020-01-09    m       30
## 221  2020-01-03    v       50
## 222  2019-12-14    x       80
## 223  2019-12-25    l        0
## 224  2019-12-28    i       10
## 225  2020-01-09    z        0
## 226  2020-01-05    g      100
## 227  2020-01-04    n       30
## 228  2019-12-26    j      100
## 229  2020-01-04    u       80
## 230  2019-12-13    o       60
## 231  2020-01-07    y       80
## 232  2019-12-16    n       50
## 233  2019-12-31    t       50
## 234  2020-01-01    r      100
## 235  2020-01-02    x       70
## 236  2019-12-27    j       60
## 237  2019-12-25    e       40
## 238  2019-12-15    z       90
## 239  2020-01-09    k       20
## 240  2019-12-29    r       50
## 241  2019-12-25    y       10
## 242  2019-12-27    p       80
## 243  2020-01-06    i       80
## 244  2019-12-19    b       40
## 245  2019-12-20    z       30
## 246  2019-12-15    z       70
## 247  2020-01-05    g       50
## 248  2019-12-27    n       50
## 249  2020-01-09    e       10
## 250  2019-12-16    h       30
## 251  2019-12-16    z      100
## 252  2019-12-24    t       10
## 253  2019-12-26    v       80
## 254  2020-01-01    c       90
## 255  2020-01-05    b       30
## 256  2019-12-30    j       60
## 257  2020-01-09    q        0
## 258  2019-12-15    m       60
## 259  2019-12-23    t       40
## 260  2020-01-08    x       70
## 261  2019-12-15    c        0
## 262  2019-12-27    n      100
## 263  2020-01-07    q       90
## 264  2020-01-01    m       80
## 265  2019-12-31    g       60
## 266  2020-01-07    j      100
## 267  2019-12-27    b       50
## 268  2020-01-08    j       60
## 269  2019-12-27    o       90
## 270  2019-12-24    r       80
## 271  2019-12-18    e       90
## 272  2019-12-14    k      100
## 273  2020-01-08    o       50
## 274  2019-12-22    l       80
## 275  2020-01-10    z       90
## 276  2020-01-10    i        0
## 277  2020-01-09    m       40
## 278  2019-12-23    l      100
## 279  2020-01-05    r       10
## 280  2019-12-21    t       70
## 281  2020-01-08    c       10
## 282  2019-12-17    o       70
## 283  2019-12-30    b        0
## 284  2019-12-13    i       30
## 285  2020-01-01    e       90
## 286  2019-12-16    l       30
## 287  2019-12-21    c       80
## 288  2020-01-01    l        0
## 289  2020-01-10    e       90
## 290  2020-01-04    x       70
## 291  2019-12-16    w       80
## 292  2019-12-18    k       40
## 293  2019-12-26    j       90
## 294  2020-01-06    o       60
## 295  2020-01-04    s      100
## 296  2019-12-30    t        0
## 297  2019-12-12    w       70
## 298  2020-01-02    d       50
## 299  2019-12-26    p       80
## 300  2019-12-25    o       20
## 301  2019-12-16    t       90
## 302  2019-12-19    t        0
## 303  2019-12-17    b       20
## 304  2020-01-04    g       30
## 305  2020-01-06    k       20
## 306  2019-12-12    g       40
## 307  2019-12-23    q       10
## 308  2019-12-16    w       30
## 309  2019-12-17    n       60
## 310  2019-12-24    e      100
## 311  2020-01-07    i       40
## 312  2019-12-14    n       70
## 313  2020-01-05    g       80
## 314  2019-12-15    f       50
## 315  2020-01-06    m       40
## 316  2019-12-22    b       90
## 317  2019-12-29    h       40
## 318  2019-12-26    q       30
## 319  2019-12-24    m       20
## 320  2020-01-05    i       20
## 321  2020-01-04    t       50
## 322  2020-01-03    c       40
## 323  2019-12-30    d       30
## 324  2019-12-17    d       90
## 325  2019-12-23    y       30
## 326  2019-12-31    l       60
## 327  2020-01-07    c       10
## 328  2020-01-04    d      100
## 329  2019-12-13    e       20
## 330  2019-12-14    n      100
## 331  2019-12-18    a       50
## 332  2019-12-24    g       40
## 333  2019-12-18    f       60
## 334  2020-01-04    z      100
## 335  2019-12-21    k      100
## 336  2020-01-01    y       60
## 337  2019-12-21    b       70
## 338  2020-01-09    g       10
## 339  2019-12-13    a       50
## 340  2019-12-16    f       20
## 341  2019-12-12    k       90
## 342  2019-12-16    e       60
## 343  2020-01-09    l       60
## 344  2019-12-31    h       70
## 345  2019-12-21    y       70
## 346  2019-12-14    z       90
## 347  2020-01-10    j       20
## 348  2019-12-15    x       70
## 349  2019-12-24    o       80
## 350  2019-12-30    j       70
## 351  2019-12-16    r       70
## 352  2020-01-06    d       10
## 353  2019-12-30    u      100
## 354  2019-12-23    g       70
## 355  2019-12-19    o        0
## 356  2019-12-25    p       90
## 357  2020-01-03    d       80
## 358  2020-01-02    s       60
## 359  2019-12-31    k       20
## 360  2019-12-12    b       80
## 361  2019-12-13    n      100
## 362  2019-12-15    x       60
## 363  2019-12-19    j        0
## 364  2019-12-13    w       60
## 365  2020-01-01    i       10
## 366  2020-01-07    a       40
## 367  2019-12-19    w      100
## 368  2019-12-18    a       30
## 369  2019-12-17    l       40
## 370  2020-01-09    d       40
## 371  2020-01-04    p       90
## 372  2020-01-08    g       20
## 373  2019-12-31    r       70
## 374  2020-01-08    e       20
## 375  2020-01-08    x       80
## 376  2020-01-10    x        0
## 377  2019-12-31    f       20
## 378  2020-01-10    v       10
## 379  2019-12-25    s       40
## 380  2019-12-30    v       10
## 381  2020-01-06    l      100
## 382  2019-12-26    l       50
## 383  2019-12-25    r       10
## 384  2020-01-06    g        0
## 385  2020-01-01    z        0
## 386  2019-12-18    v       90
## 387  2020-01-05    p       10
## 388  2019-12-17    u       90
## 389  2019-12-21    a       90
## 390  2020-01-10    i       80
## 391  2019-12-14    q       10
## 392  2019-12-21    w       30
## 393  2019-12-22    b       40
## 394  2019-12-25    u       70
## 395  2019-12-18    i       20
## 396  2019-12-14    a      100
## 397  2019-12-29    s       10
## 398  2019-12-19    n       80
## 399  2019-12-15    n      100
## 400  2019-12-21    f        0
## 401  2020-01-01    x      100
## 402  2020-01-03    z       20
## 403  2020-01-05    v       20
## 404  2019-12-18    m       30
## 405  2019-12-26    y        0
## 406  2020-01-10    f       50
## 407  2019-12-21    j       80
## 408  2019-12-17    p       50
## 409  2020-01-01    p       90
## 410  2020-01-06    y       50
## 411  2020-01-05    a       50
## 412  2020-01-01    y       90
## 413  2020-01-04    z       30
## 414  2019-12-31    h       10
## 415  2019-12-15    m       40
## 416  2019-12-21    i      100
## 417  2019-12-15    f       80
## 418  2019-12-15    f       90
## 419  2019-12-14    q       50
## 420  2019-12-15    j       70
## 421  2020-01-01    f       70
## 422  2019-12-17    i       80
## 423  2019-12-20    t      100
## 424  2019-12-31    t        0
## 425  2020-01-03    z       50
## 426  2020-01-09    m       40
## 427  2019-12-24    g       40
## 428  2019-12-17    g       30
## 429  2019-12-18    m        0
## 430  2019-12-30    y       10
## 431  2020-01-09    o       60
## 432  2020-01-03    y       90
## 433  2019-12-24    h       50
## 434  2019-12-17    m       70
## 435  2020-01-06    v       80
## 436  2019-12-21    h       90
## 437  2020-01-05    e       10
## 438  2019-12-28    a       70
## 439  2019-12-14    w       10
## 440  2019-12-15    n       50
## 441  2019-12-15    u        0
## 442  2019-12-28    b        0
## 443  2019-12-24    g       20
## 444  2019-12-20    v       80
## 445  2019-12-13    v       20
## 446  2019-12-23    x       20
## 447  2019-12-12    a       90
## 448  2019-12-27    b       90
## 449  2019-12-22    x        0
## 450  2020-01-07    e       90
## 451  2019-12-16    y        0
## 452  2019-12-24    d       10
## 453  2019-12-26    b       50
## 454  2020-01-06    k       90
## 455  2019-12-13    u       70
## 456  2019-12-23    y       70
## 457  2019-12-24    a       80
## 458  2019-12-21    c       90
## 459  2020-01-04    n       70
## 460  2020-01-01    l       70
## 461  2019-12-13    q       80
## 462  2020-01-02    d       70
## 463  2019-12-21    u       30
## 464  2019-12-16    n       70
## 465  2019-12-16    d       10
## 466  2020-01-01    t       10
## 467  2019-12-25    v        0
## 468  2019-12-15    b       30
## 469  2019-12-31    b       30
## 470  2019-12-15    y       10
## 471  2019-12-29    z        0
## 472  2019-12-18    f       30
## 473  2019-12-22    g       10
## 474  2019-12-20    x       20
## 475  2019-12-12    c       30
## 476  2019-12-16    c       50
## 477  2019-12-12    a       10
## 478  2020-01-04    a      100
## 479  2020-01-08    y       20
## 480  2020-01-06    d        0
## 481  2019-12-27    q       60
## 482  2019-12-31    z       50
## 483  2019-12-24    x       30
## 484  2020-01-09    u       20
## 485  2019-12-17    s       10
## 486  2020-01-02    f       40
## 487  2020-01-09    l       10
## 488  2020-01-08    g       70
## 489  2019-12-22    r       70
## 490  2020-01-05    v       90
## 491  2019-12-18    f       90
## 492  2019-12-13    f       30
## 493  2019-12-12    x       10
## 494  2019-12-14    h       70
## 495  2020-01-03    v       60
## 496  2019-12-20    q       10
## 497  2020-01-02    b       20
## 498  2019-12-27    c       30
## 499  2020-01-02    b       20
## 500  2019-12-17    d        0
## 501  2020-01-06    h       50
## 502  2020-01-03    e        0
## 503  2019-12-28    a      100
## 504  2019-12-29    q       30
## 505  2019-12-13    r       30
## 506  2019-12-29    s       30
## 507  2020-01-04    i       50
## 508  2019-12-27    x       30
## 509  2019-12-25    f       20
## 510  2019-12-29    h      100
## 511  2019-12-27    v       10
## 512  2020-01-08    t       50
## 513  2019-12-17    r       90
## 514  2020-01-08    f       20
## 515  2019-12-13    r       40
## 516  2019-12-16    r       80
## 517  2020-01-08    m       20
## 518  2019-12-16    m        0
## 519  2019-12-31    d        0
## 520  2019-12-21    a       30
## 521  2019-12-25    k      100
## 522  2019-12-20    q       90
## 523  2020-01-06    w        0
## 524  2020-01-05    t       70
## 525  2019-12-25    h       90
## 526  2019-12-26    y       70
## 527  2019-12-23    q       90
## 528  2019-12-14    c       90
## 529  2019-12-13    l       10
## 530  2020-01-07    r       40
## 531  2019-12-19    p       90
## 532  2020-01-07    h       20
## 533  2020-01-04    k       50
## 534  2019-12-26    y      100
## 535  2020-01-06    t        0
## 536  2019-12-20    p       10
## 537  2019-12-23    q       40
## 538  2019-12-28    c       10
## 539  2019-12-13    t      100
## 540  2019-12-27    a       80
## 541  2020-01-04    g       60
## 542  2020-01-01    s       30
## 543  2019-12-28    j      100
## 544  2019-12-13    t        0
## 545  2019-12-29    n       30
## 546  2019-12-13    r       40
## 547  2019-12-14    r      100
## 548  2019-12-13    v       10
## 549  2020-01-08    g       10
## 550  2020-01-08    a       90
## 551  2019-12-30    o       70
## 552  2019-12-29    c        0
## 553  2020-01-02    r       90
## 554  2019-12-17    e       30
## 555  2020-01-09    n       30
## 556  2020-01-10    b       40
## 557  2019-12-27    e       70
## 558  2019-12-17    t       50
## 559  2019-12-20    c       50
## 560  2020-01-04    n        0
## 561  2020-01-03    l       70
## 562  2020-01-05    c       30
## 563  2019-12-27    h       50
## 564  2019-12-21    u       90
## 565  2019-12-19    l       80
## 566  2019-12-31    l      100
## 567  2019-12-22    e      100
## 568  2020-01-08    g       20
## 569  2019-12-31    d       20
## 570  2019-12-28    f       60
## 571  2019-12-12    i       50
## 572  2019-12-14    m       60
## 573  2020-01-04    q       90
## 574  2020-01-05    u        0
## 575  2020-01-06    z       60
## 576  2020-01-10    p      100
## 577  2019-12-20    t       50
## 578  2019-12-18    y       10
## 579  2019-12-22    w       90
## 580  2019-12-21    r       90
## 581  2020-01-09    o       30
## 582  2019-12-13    c       60
## 583  2019-12-25    h       20
## 584  2019-12-16    d        0
## 585  2020-01-02    s       10
## 586  2020-01-10    y       80
## 587  2020-01-10    w      100
## 588  2019-12-14    a       10
## 589  2019-12-24    u       60
## 590  2019-12-30    x       70
## 591  2020-01-08    l       40
## 592  2020-01-01    l       60
## 593  2019-12-31    e       80
## 594  2019-12-29    h       60
## 595  2019-12-29    a       60
## 596  2019-12-23    u       20
## 597  2020-01-08    v       10
## 598  2019-12-27    z      100
## 599  2020-01-03    m       50
## 600  2019-12-22    o       30
## 601  2019-12-13    y       80
## 602  2020-01-01    t       30
## 603  2019-12-15    j       40
## 604  2020-01-03    w       90
## 605  2019-12-27    a       70
## 606  2020-01-04    f       60
## 607  2019-12-17    s       20
## 608  2020-01-09    b      100
## 609  2019-12-22    t       50
## 610  2020-01-09    t       10
## 611  2019-12-22    z       40
## 612  2019-12-29    h        0
## 613  2020-01-02    i       30
## 614  2019-12-27    e       20
## 615  2019-12-23    d       50
## 616  2019-12-17    u        0
## 617  2020-01-04    x       80
## 618  2019-12-28    f       30
## 619  2019-12-18    w       30
## 620  2020-01-01    n       50
## 621  2019-12-19    p       80
## 622  2019-12-30    m       80
## 623  2019-12-25    e       50
## 624  2019-12-19    b       10
## 625  2020-01-02    l       40
## 626  2019-12-20    r       90
## 627  2019-12-19    n        0
## 628  2019-12-22    b       10
## 629  2020-01-08    q       80
## 630  2019-12-30    i       50
## 631  2020-01-03    w       70
## 632  2019-12-15    s      100
## 633  2019-12-21    c       40
## 634  2019-12-13    p       10
## 635  2019-12-26    k       90
## 636  2019-12-28    f       70
## 637  2020-01-10    r        0
## 638  2019-12-19    m       90
## 639  2020-01-09    j       60
## 640  2019-12-13    g       50
## 641  2019-12-17    g       10
## 642  2020-01-09    i       50
## 643  2020-01-03    n      100
## 644  2019-12-23    s       20
## 645  2019-12-14    b       90
## 646  2020-01-08    i       80
## 647  2019-12-12    t       60
## 648  2019-12-24    j       60
## 649  2019-12-23    z       80
## 650  2020-01-09    v       30
## 651  2020-01-02    q       40
## 652  2019-12-25    c       60
## 653  2020-01-07    w       90
## 654  2019-12-17    i       40
## 655  2019-12-13    b        0
## 656  2019-12-21    i       20
## 657  2019-12-23    x       40
## 658  2019-12-19    j       70
## 659  2019-12-21    i      100
## 660  2019-12-21    t       90
## 661  2020-01-09    w       20
## 662  2019-12-31    v       60
## 663  2020-01-07    x       70
## 664  2019-12-25    e       70
## 665  2019-12-30    q       60
## 666  2020-01-10    g       50
## 667  2019-12-17    e        0
## 668  2020-01-04    t       20
## 669  2019-12-20    a      100
## 670  2019-12-28    v       60
## 671  2019-12-30    c       90
## 672  2019-12-23    h       70
## 673  2019-12-25    w       10
## 674  2020-01-05    o       60
## 675  2019-12-27    c       90
## 676  2019-12-31    n       10
## 677  2019-12-17    y      100
## 678  2019-12-29    p       10
## 679  2019-12-21    g       40
## 680  2020-01-08    w       60
## 681  2019-12-19    b       50
## 682  2019-12-15    m       90
## 683  2020-01-06    c       90
## 684  2019-12-28    m       10
## 685  2020-01-02    y       60
## 686  2020-01-05    d       80
## 687  2019-12-24    n        0
## 688  2019-12-23    g        0
## 689  2019-12-22    q       80
## 690  2019-12-28    s       30
## 691  2019-12-30    m       50
## 692  2019-12-29    f       10
## 693  2019-12-20    v       30
## 694  2019-12-16    q       80
## 695  2019-12-30    k       50
## 696  2020-01-09    d        0
## 697  2020-01-03    w       60
## 698  2019-12-25    m       80
## 699  2019-12-20    f       80
## 700  2019-12-17    l       40
## 701  2019-12-25    d      100
## 702  2019-12-20    f       90
## 703  2019-12-28    w      100
## 704  2019-12-13    c       60
## 705  2020-01-08    e       90
## 706  2020-01-02    q       30
## 707  2019-12-24    m       50
## 708  2019-12-28    i      100
## 709  2020-01-09    s        0
## 710  2020-01-05    z       30
## 711  2020-01-08    w       50
## 712  2020-01-02    d        0
## 713  2019-12-29    i       90
## 714  2019-12-14    f        0
## 715  2019-12-26    s       20
## 716  2019-12-19    p       20
## 717  2020-01-10    h       80
## 718  2019-12-13    k       90
## 719  2019-12-25    i        0
## 720  2020-01-10    i       80
## 721  2020-01-02    r       70
## 722  2020-01-10    t       90
## 723  2019-12-24    v        0
## 724  2019-12-28    x       10
## 725  2019-12-24    t       60
## 726  2019-12-16    a       20
## 727  2020-01-03    r       70
## 728  2020-01-07    n       50
## 729  2019-12-28    j       10
## 730  2019-12-12    r       20
## 731  2019-12-21    w        0
## 732  2020-01-06    u       70
## 733  2019-12-28    e      100
## 734  2019-12-12    i       70
## 735  2020-01-09    n       80
## 736  2020-01-05    k       60
## 737  2019-12-30    d       60
## 738  2019-12-23    y       20
## 739  2019-12-29    q       70
## 740  2019-12-23    x        0
## 741  2019-12-27    l       70
## 742  2020-01-08    f       40
## 743  2020-01-06    t      100
## 744  2019-12-18    c       80
## 745  2020-01-07    t       40
## 746  2019-12-25    h       60
## 747  2019-12-25    z       50
## 748  2020-01-09    l       30
## 749  2020-01-08    w       50
## 750  2020-01-06    r       70
## 751  2019-12-16    g       70
## 752  2019-12-14    b       40
## 753  2019-12-28    x       10
## 754  2020-01-09    q       30
## 755  2020-01-05    l       20
## 756  2020-01-01    f      100
## 757  2020-01-02    l       30
## 758  2020-01-04    n       10
## 759  2019-12-30    x       80
## 760  2020-01-08    z       50
## 761  2019-12-23    u       60
## 762  2020-01-05    l       70
## 763  2019-12-21    g       20
## 764  2019-12-16    r       40
## 765  2020-01-10    z       10
## 766  2020-01-02    u       50
## 767  2019-12-26    q       30
## 768  2019-12-12    h       70
## 769  2019-12-21    k       80
## 770  2020-01-05    p       40
## 771  2019-12-23    l       10
## 772  2019-12-29    k       20
## 773  2020-01-08    b       40
## 774  2020-01-05    p       40
## 775  2019-12-29    g      100
## 776  2019-12-14    d       90
## 777  2019-12-26    r       40
## 778  2019-12-16    t       10
## 779  2020-01-10    w       20
## 780  2019-12-17    k      100
## 781  2019-12-28    m       80
## 782  2019-12-26    y      100
## 783  2019-12-22    h       90
## 784  2020-01-03    e       90
## 785  2020-01-06    f       80
## 786  2019-12-12    q        0
## 787  2019-12-27    e       90
## 788  2020-01-05    c       30
## 789  2019-12-16    f       80
## 790  2019-12-27    h        0
## 791  2019-12-19    h      100
## 792  2019-12-24    n      100
## 793  2019-12-25    s       90
## 794  2020-01-10    s      100
## 795  2019-12-19    b       70
## 796  2019-12-13    p       80
## 797  2019-12-22    a       40
## 798  2020-01-03    v       80
## 799  2019-12-24    f        0
## 800  2019-12-14    x       40
## 801  2019-12-15    g       80
## 802  2019-12-16    h      100
## 803  2019-12-17    a       10
## 804  2019-12-31    g       40
## 805  2019-12-12    y       10
## 806  2020-01-04    z       70
## 807  2019-12-31    q       60
## 808  2019-12-19    t       30
## 809  2019-12-22    c       40
## 810  2019-12-29    d      100
## 811  2019-12-20    k        0
## 812  2019-12-16    a       30
## 813  2020-01-07    o       60
## 814  2019-12-26    k       20
## 815  2019-12-26    o      100
## 816  2020-01-03    o       50
## 817  2019-12-26    z       20
## 818  2019-12-23    l       10
## 819  2020-01-02    f       30
## 820  2019-12-28    r       70
## 821  2020-01-07    a       10
## 822  2019-12-13    z      100
## 823  2019-12-22    m      100
## 824  2020-01-07    r        0
## 825  2019-12-28    y       40
## 826  2020-01-04    u       60
## 827  2019-12-27    b       60
## 828  2019-12-26    j       50
## 829  2019-12-23    h       80
## 830  2019-12-29    c       50
## 831  2019-12-24    b        0
## 832  2019-12-23    w       10
## 833  2020-01-08    o        0
## 834  2019-12-12    v       40
## 835  2019-12-19    j       90
## 836  2019-12-16    t       80
## 837  2019-12-23    f       70
## 838  2019-12-28    g       70
## 839  2019-12-28    a       80
## 840  2019-12-24    y      100
## 841  2019-12-17    g       30
## 842  2020-01-09    r       90
## 843  2019-12-23    t       60
## 844  2019-12-19    n       40
## 845  2019-12-12    u       60
## 846  2019-12-30    e      100
## 847  2019-12-21    a       30
## 848  2020-01-10    y      100
## 849  2019-12-17    c      100
## 850  2020-01-09    u       20
## 851  2020-01-10    u       20
## 852  2020-01-01    p       10
## 853  2019-12-20    z       60
## 854  2020-01-07    g       30
## 855  2019-12-20    z       70
## 856  2019-12-14    c       90
## 857  2019-12-12    s        0
## 858  2020-01-07    k       60
## 859  2019-12-19    g       30
## 860  2019-12-27    e       80
## 861  2019-12-23    i       10
## 862  2020-01-04    w      100
## 863  2019-12-24    n       90
## 864  2020-01-04    e        0
## 865  2020-01-02    l       60
## 866  2020-01-09    c       50
## 867  2019-12-31    o       30
## 868  2019-12-25    g        0
## 869  2019-12-16    o       60
## 870  2019-12-13    r       10
## 871  2019-12-25    y       30
## 872  2020-01-08    t       60
## 873  2019-12-24    v       30
## 874  2020-01-07    b       80
## 875  2020-01-08    z       70
## 876  2020-01-01    v       40
## 877  2020-01-09    g      100
## 878  2019-12-15    r       10
## 879  2019-12-27    u       40
## 880  2019-12-18    r       30
## 881  2020-01-04    y      100
## 882  2019-12-16    f       60
## 883  2019-12-22    t      100
## 884  2020-01-10    l       40
## 885  2020-01-06    n       50
## 886  2019-12-20    d      100
## 887  2019-12-18    h      100
## 888  2019-12-19    d       50
## 889  2019-12-28    w       60
## 890  2019-12-27    z       10
## 891  2020-01-01    d       60
## 892  2019-12-27    l       20
## 893  2019-12-22    t       20
## 894  2020-01-07    n       30
## 895  2020-01-09    g       30
## 896  2019-12-26    z       50
## 897  2019-12-25    i       50
## 898  2020-01-08    q       60
## 899  2019-12-15    v       90
## 900  2019-12-25    q       30
## 901  2019-12-19    k       60
## 902  2019-12-26    p       90
## 903  2019-12-15    n        0
## 904  2019-12-22    c       30
## 905  2019-12-24    z       70
## 906  2019-12-20    t       10
## 907  2019-12-31    y       90
## 908  2019-12-15    p       30
## 909  2020-01-06    n       40
## 910  2020-01-08    u       50
## 911  2019-12-25    o       10
## 912  2020-01-03    d        0
## 913  2020-01-08    u      100
## 914  2020-01-08    k        0
## 915  2019-12-14    x       30
## 916  2019-12-20    o      100
## 917  2020-01-08    r       90
## 918  2019-12-31    d       50
## 919  2019-12-19    w      100
## 920  2019-12-22    x       30
## 921  2020-01-06    k       70
## 922  2020-01-02    o       90
## 923  2019-12-19    x       90
## 924  2020-01-06    x       70
## 925  2019-12-13    v       90
## 926  2019-12-30    i       80
## 927  2019-12-17    t       10
## 928  2019-12-15    z       40
## 929  2020-01-01    v       50
## 930  2020-01-01    j       40
## 931  2020-01-07    y        0
## 932  2020-01-08    m      100
## 933  2020-01-03    u       20
## 934  2019-12-16    o       90
## 935  2019-12-14    d       20
## 936  2020-01-01    z       80
## 937  2019-12-30    n       80
## 938  2019-12-26    z       80
## 939  2019-12-28    x       60
## 940  2019-12-22    v       30
## 941  2019-12-21    p       40
## 942  2020-01-06    o       40
## 943  2019-12-28    t       80
## 944  2019-12-27    k       50
## 945  2019-12-27    m       60
## 946  2020-01-03    e       10
## 947  2020-01-04    t       10
## 948  2019-12-16    q       10
## 949  2019-12-20    w       40
## 950  2019-12-30    h        0
## 951  2020-01-04    l       40
## 952  2020-01-07    r      100
## 953  2019-12-24    y       70
## 954  2019-12-17    p       80
## 955  2020-01-05    n       90
## 956  2019-12-19    b      100
## 957  2020-01-03    a       40
## 958  2020-01-09    o      100
## 959  2020-01-02    x       70
## 960  2019-12-14    n        0
## 961  2019-12-27    q       30
## 962  2019-12-27    m       60
## 963  2020-01-08    y       20
## 964  2020-01-04    g        0
## 965  2019-12-22    f       80
## 966  2020-01-05    l       40
## 967  2020-01-01    d       20
## 968  2019-12-24    x       40
## 969  2019-12-12    v       40
## 970  2019-12-20    d       70
## 971  2020-01-07    m        0
## 972  2020-01-04    h       20
## 973  2019-12-12    h       40
## 974  2020-01-08    t       30
## 975  2020-01-05    y       90
## 976  2019-12-29    t       40
## 977  2019-12-16    o       80
## 978  2020-01-03    f       20
## 979  2019-12-17    f       80
## 980  2019-12-15    g       20
## 981  2019-12-23    u       60
## 982  2019-12-30    v      100
## 983  2019-12-18    f       80
## 984  2019-12-24    r        0
## 985  2019-12-21    r       90
## 986  2019-12-18    t       20
## 987  2019-12-28    b       80
## 988  2019-12-23    v        0
## 989  2019-12-14    a        0
## 990  2020-01-03    h       80
## 991  2019-12-19    a        0
## 992  2019-12-13    s       60
## 993  2019-12-25    j        0
## 994  2019-12-15    j       40
## 995  2019-12-24    g       60
## 996  2019-12-31    u       20
## 997  2019-12-16    n       20
## 998  2019-12-26    f       50
## 999  2019-12-22    u       20
## 1000 2019-12-21    t       20
```

---

- Warns you when you make mistakes (!):

```r
tib1$quanitty
```

<pre style="color: red;"><code>## Warning: Unknown or uninitialised column: 'quanitty'.
</code></pre>

```
## NULL
```

```r
df1$quanitty
```

```
## NULL
```

---

- Can also create via `tribble()`:

```r
tribble(
  ~a, ~b, ~c,
  "a", 1, 2.2,
  "b", 2, 4.3,
  "c", 3, 3.4
)
```

```
## # A tibble: 3 x 3
##   a         b     c
##   <chr> <dbl> <dbl>
## 1 a         1   2.2
## 2 b         2   4.3
## 3 c         3   3.4
```

---

- Can build on top variables during creation:

```r
tibble(x = 1:5, y = x^2)
```

```
## # A tibble: 5 x 2
##       x     y
##   <int> <dbl>
## 1     1     1
## 2     2     4
## 3     3     9
## 4     4    16
## 5     5    25
```

```r
data.frame(x = 1:5, y = x^2)
```

<pre style="color: red;"><code>## Error in data.frame(x = 1:5, y = x^2): object 'x' not found
</code></pre>

---

- Will never turn your strings into factors, will never change your column names:

```r
tib1 <- readr::read_csv("../data/bad_args_test.csv", col_types = cols())
colnames(tib1)
```

```
## [1] "col1" "col2" "col3"
```

```r
tib1$col3
```

```
## [1] "a" "b" "c" "d"
```

```r
df1 <- read.csv("../data/bad_args_test.csv")
colnames(df1)
```

```
## [1] "ï..col1" "col2"    "col3"
```

```r
df1$col3
```

```
## [1] a b c d
## Levels: a b c d
```

---

Though one ought to remember a `tibble` is still a `data.frame`:

```r
class(tib1)
```

```
## [1] "spec_tbl_df" "tbl_df"      "tbl"         "data.frame"
```

```r
class(df1)
```

```
## [1] "data.frame"
```

---
class: section-slide

# End of Detour

---

## Consistency - Example: `stringr`

> a cohesive set of functions designed to make working with strings as easy as possible.

```r
strings_vec <- c("I'm feeling fine", "I'm perfectly OK",
                 "Nothing is wrong!")
str_length(strings_vec)
```

```
## [1] 16 16 17
```

```r
str_c(strings_vec, collapse = ", ")
```

```
## [1] "I'm feeling fine, I'm perfectly OK, Nothing is wrong!"
```

```r
str_sub(strings_vec, 1, 3)
```

```
## [1] "I'm" "I'm" "Not"
```

---

```r
str_detect(strings_vec, "I'm")
```

```
## [1]  TRUE  TRUE FALSE
```

```r
str_replace(strings_vec, "I'm", "You're")
```

```
## [1] "You're feeling fine" "You're perfectly OK" "Nothing is wrong!"
```

```r
str_split("Do you know regex?", " ")
```

```
## [[1]]
## [1] "Do"     "you"    "know"   "regex?"
```

```r
str_extract(strings_vec, "[aeiou]")
```

```
## [1] "e" "e" "o"
```

```r
str_count(strings_vec, "[A-Z]")
```

```
## [1] 1 3 1
```

---

## The Pipe

Remember you?

data.frame(orientation = c("bisexual", "gay", "straight"),
           income_mean = c(mean_bi, mean_gay, mean_straight))
```

```
##   orientation income_mean
## 1    bisexual   133421.05
## 2         gay    86489.36
## 3    straight    85219.74
```

---

Doesn't this make much more sense?

```r
okcupid %>%
  filter(sex == "f", age > 30) %>%
  group_by(orientation) %>%
  summarize(income_mean = mean(income, na.rm = TRUE))
```

```
## # A tibble: 3 x 2
##   orientation income_mean
##   <chr>             <dbl>
## 1 bisexual        133421.
## 2 gay              86489.
## 3 straight         85220.
```

- Read as:
  - Take the OKCupid data,
  - Filter only women above the age of 30,
  - And for each group of sexual orientation,
  - Give me the average income

---

- Make verbs, not nouns
- Can always access the dataset last stage with "`.`":

```r
okcupid %>%
  filter(str_count(essay0) > median(str_count(.$essay0), na.rm = T))
```
- Operates not just on data frames or tibbles:

```r
strings_vec %>% str_to_title()
```

```
## [1] "I'm Feeling Fine"  "I'm Perfectly Ok"  "Nothing Is Wrong!"
```
- No intermediate objects
- Don't strive to make the longest possible pipe (though it is a fun experiment)
- Tools exist for debugging

---

And, if you want to throw in the n, the median:

```r
okcupid %>%
  filter(sex == "f", age > 30) %>%
  group_by(orientation) %>%
  summarize(income_mean = mean(income, na.rm = TRUE),
            income_median = median(income, na.rm = TRUE),
            n = n())
```

```
## # A tibble: 3 x 4
##   orientation income_mean income_median     n
##   <chr>             <dbl>         <dbl> <int>
## 1 bisexual        133421.         50000   652
## 2 gay              86489.         40000   664
## 3 straight         85220.         60000 10436
```

---

And if you want this for the age as well:

```r
okcupid %>%
  filter(sex == "f", age > 30) %>%
  group_by(orientation) %>%
  summarize_at(vars(income, age),
               list(mean = mean, median = median), na.rm = TRUE)
```

```
## # A tibble: 3 x 5
##   orientation income_mean age_mean income_median age_median
##   <chr>             <dbl>    <dbl>         <dbl>      <dbl>
## 1 bisexual        133421.     37.8         50000         36
## 2 gay              86489.     40.4         40000         38
## 3 straight         85220.     40.7         60000         38
```

Now *this* is a language for Data Science.

But we're getting ahead of ourselves.

---

## `ggplot2`

.font80percent[
[Ave Mariah / Giora Simchoni](http://giorasimchoni.com/2017/12/10/2017-12-10-ave-mariah/)
]
---

## `ggplot2`

.font80percent[
[Soviet Space Dogs / David Smale](https://davidsmale.netlify.com/portfolio/soviet-space-dogs-part-2/)
]
---

## `ggplot2`

.font80percent[
[Federer, Nadal, Djokovic and Murray, Love. / Giora Simchoni](http://giorasimchoni.com/2017/05/01/2017-05-01-federer-nadal-djokovic-and-murray-love/)
]
---

## `ggplot2`

.font80percent[
[NYT-style urban heat island maps / Katie Jolly](https://www.katiejolly.io/blog/2019-08-28/nyt-urban-heat)
]
---

## `ggplot2`

.font80percent[
[A map of marriage rates, state by state / Unkown](https://www.r-graph-gallery.com/328-hexbin-map-of-the-usa.html)
]
---

## `ggplot2`

.font80percent[
[Calendar-based graphics for visualizing people’s daily schedules / Earo Wang](https://pdf.earo.me/calendar-vis.pdf)
]
---

## The Community

.pull-left[
- 100% Open Source on Github
- Cheatsheet for everything
- Documentation for humans, Packages websites, Webinars, Free Books (start with [R4DS](https://r4ds.had.co.nz/))
- [Rstudio Community forum](https://community.rstudio.com/)
- [RLadies](https://rladies.org/) worldwide branches .font80percent[(who will pick up the 🥊 and create RLadies TLV?)]
- Very strong on Twitter [#rstats](https://twitter.com/search?q=%23rstats)
]

.pull-right[
<a href="https://rstudio.com/resources/cheatsheets/"><img src="images/stringr_cheatsheet.png" style="width: 100%" /></a>
]