Ex. 2.3: Building Your Plot

class: center, middle, inverse, title-slide

# Ex. 2.3: Building Your Plot
## Line Plot

---

count: false

.panel1-the_chunk-auto[

```r
*employed_under_150K
```
]
 
.panel2-the_chunk-auto[

```
# A tibble: 80,635 x 5
   Earnings Earnings_per_member Sex     Age Education              
      <dbl>               <dbl> <chr> <dbl> <chr>                  
 1     8000               1600  F        20 Less than HS           
 2     4000                800  M        16 Less than HS           
 3    17350               8675  M        27 Less than HS           
 4    12000               6000  M        24 Less than HS           
 5    25480              25480  M        62 Bachelors              
 6     6000               1000  F        53 Bachelors              
 7    70200              11700  M        52 Bachelors              
 8    10520               1753. F        16 Less than HS           
 9    46000              11500  F        31 Some College/Associates
10    40000              40000  M        37 Less than HS           
# … with 80,625 more rows
```
]

---
count: false

.panel1-the_chunk-auto[

```r
employed_under_150K %>%
* group_by(Age)
```
]
 
.panel2-the_chunk-auto[

```
# A tibble: 80,635 x 5
# Groups:   Age [67]
   Earnings Earnings_per_member Sex     Age Education              
      <dbl>               <dbl> <chr> <dbl> <chr>                  
 1     8000               1600  F        20 Less than HS           
 2     4000                800  M        16 Less than HS           
 3    17350               8675  M        27 Less than HS           
 4    12000               6000  M        24 Less than HS           
 5    25480              25480  M        62 Bachelors              
 6     6000               1000  F        53 Bachelors              
 7    70200              11700  M        52 Bachelors              
 8    10520               1753. F        16 Less than HS           
 9    46000              11500  F        31 Some College/Associates
10    40000              40000  M        37 Less than HS           
# … with 80,625 more rows
```
]

---
count: false

.panel1-the_chunk-auto[

```r
employed_under_150K %>%
  group_by(Age) %>%
* summarise(Median = median(Earnings))
```
]
 
.panel2-the_chunk-auto[

```
# A tibble: 67 x 2
     Age Median
   <dbl>  <dbl>
 1    15   1500
 2    16   2000
 3    17   3000
 4    18   5000
 5    19   8550
 6    20  11000
 7    21  15000
 8    22  17960
 9    23  20800
10    24  24000
# … with 57 more rows
```
]

---
count: false

.panel1-the_chunk-auto[

```r
employed_under_150K %>%
  group_by(Age) %>%
  summarise(Median = median(Earnings)) %>%
* ggplot()
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_04_output-1.png" width="576" />
]

---
count: false

.panel1-the_chunk-auto[

```r
employed_under_150K %>%
  group_by(Age) %>%
  summarise(Median = median(Earnings)) %>%
  ggplot() +
* aes(x = Age)
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_05_output-1.png" width="576" />
]

---
count: false

.panel1-the_chunk-auto[

```r
employed_under_150K %>%
  group_by(Age) %>%
  summarise(Median = median(Earnings)) %>%
  ggplot() +
  aes(x = Age) +
* aes(y = Median)
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_06_output-1.png" width="576" />
]

---
count: false

.panel1-the_chunk-auto[

```r
employed_under_150K %>%
  group_by(Age) %>%
  summarise(Median = median(Earnings)) %>%
  ggplot() +
  aes(x = Age) +
  aes(y = Median) +
* geom_line()
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_07_output-1.png" width="576" />
]

---
count: false

.panel1-the_chunk-auto[

```r
employed_under_150K %>%
  group_by(Age) %>%
  summarise(Median = median(Earnings)) %>%
  ggplot() +
  aes(x = Age) +
  aes(y = Median) +
  geom_line() +
* labs(x="Age (Years)")
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_08_output-1.png" width="576" />
]

---
count: false

.panel1-the_chunk-auto[

```r
employed_under_150K %>%
  group_by(Age) %>%
  summarise(Median = median(Earnings)) %>%
  ggplot() +
  aes(x = Age) +
  aes(y = Median) +
  geom_line() +
  labs(x="Age (Years)") +
* labs(y="Earnings (USD)")
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_09_output-1.png" width="576" />
]

---
count: false

.panel1-the_chunk-auto[

```r
employed_under_150K %>%
  group_by(Age) %>%
  summarise(Median = median(Earnings)) %>%
  ggplot() +
  aes(x = Age) +
  aes(y = Median) +
  geom_line() +
  labs(x="Age (Years)") +
  labs(y="Earnings (USD)") +
* labs(title = "Age vs. Median Earnings")
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_10_output-1.png" width="576" />
]

---
count: false

.panel1-the_chunk-auto[

*employed_under_150K
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_11_output-1.png" width="576" />

---
count: false

.panel1-the_chunk-auto[

employed_under_150K %>%
* group_by(Age, Sex)
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_12_output-1.png" width="576" />

```
# A tibble: 80,635 x 5
# Groups:   Age, Sex [134]
   Earnings Earnings_per_member Sex     Age Education              
      <dbl>               <dbl> <chr> <dbl> <chr>                  
 1     8000               1600  F        20 Less than HS           
 2     4000                800  M        16 Less than HS           
 3    17350               8675  M        27 Less than HS           
 4    12000               6000  M        24 Less than HS           
 5    25480              25480  M        62 Bachelors              
 6     6000               1000  F        53 Bachelors              
 7    70200              11700  M        52 Bachelors              
 8    10520               1753. F        16 Less than HS           
 9    46000              11500  F        31 Some College/Associates
10    40000              40000  M        37 Less than HS           
# … with 80,625 more rows
```
]

---
count: false

.panel1-the_chunk-auto[

employed_under_150K %>%
  group_by(Age, Sex) %>%
* summarise(Median = median(Earnings))
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_13_output-1.png" width="576" />

```
# A tibble: 134 x 3
# Groups:   Age [67]
     Age Sex   Median
   <dbl> <chr>  <dbl>
 1    15 F      1500 
 2    15 M      1500 
 3    16 F      2000 
 4    16 M      2000 
 5    17 F      2880 
 6    17 M      3200 
 7    18 F      4600 
 8    18 M      5000 
 9    19 F      7626.
10    19 M     10000 
# … with 124 more rows
```
]

---
count: false

.panel1-the_chunk-auto[

employed_under_150K %>%
  group_by(Age, Sex) %>%
  summarise(Median = median(Earnings)) %>%
* ggplot()
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_14_output-1.png" width="576" /><img src="ex2.3_embed_files/figure-html/the_chunk_auto_14_output-2.png" width="576" />
]

---
count: false

.panel1-the_chunk-auto[

employed_under_150K %>%
  group_by(Age, Sex) %>%
  summarise(Median = median(Earnings)) %>%
  ggplot() +
* aes(x = Age)
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_15_output-1.png" width="576" /><img src="ex2.3_embed_files/figure-html/the_chunk_auto_15_output-2.png" width="576" />
]

---
count: false

.panel1-the_chunk-auto[

employed_under_150K %>%
  group_by(Age, Sex) %>%
  summarise(Median = median(Earnings)) %>%
  ggplot() +
  aes(x = Age) +
* aes(y = Median)
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_16_output-1.png" width="576" /><img src="ex2.3_embed_files/figure-html/the_chunk_auto_16_output-2.png" width="576" />
]

---
count: false

.panel1-the_chunk-auto[

employed_under_150K %>%
  group_by(Age, Sex) %>%
  summarise(Median = median(Earnings)) %>%
  ggplot() +
  aes(x = Age) +
  aes(y = Median) +
* aes(color = Sex)
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_17_output-1.png" width="576" /><img src="ex2.3_embed_files/figure-html/the_chunk_auto_17_output-2.png" width="576" />
]

---
count: false

.panel1-the_chunk-auto[

employed_under_150K %>%
  group_by(Age, Sex) %>%
  summarise(Median = median(Earnings)) %>%
  ggplot() +
  aes(x = Age) +
  aes(y = Median) +
  aes(color = Sex) +
* geom_line()
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_18_output-1.png" width="576" /><img src="ex2.3_embed_files/figure-html/the_chunk_auto_18_output-2.png" width="576" />
]

---
count: false

.panel1-the_chunk-auto[

employed_under_150K %>%
  group_by(Age, Sex) %>%
  summarise(Median = median(Earnings)) %>%
  ggplot() +
  aes(x = Age) +
  aes(y = Median) +
  aes(color = Sex) +
  geom_line() +
* labs(x="Age (Years)")
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_19_output-1.png" width="576" /><img src="ex2.3_embed_files/figure-html/the_chunk_auto_19_output-2.png" width="576" />
]

---
count: false

.panel1-the_chunk-auto[

employed_under_150K %>%
  group_by(Age, Sex) %>%
  summarise(Median = median(Earnings)) %>%
  ggplot() +
  aes(x = Age) +
  aes(y = Median) +
  aes(color = Sex) +
  geom_line() +
  labs(x="Age (Years)") +
* labs(y="Earnings (USD)")
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_20_output-1.png" width="576" /><img src="ex2.3_embed_files/figure-html/the_chunk_auto_20_output-2.png" width="576" />
]

---
count: false

.panel1-the_chunk-auto[

employed_under_150K %>%
  group_by(Age, Sex) %>%
  summarise(Median = median(Earnings)) %>%
  ggplot() +
  aes(x = Age) +
  aes(y = Median) +
  aes(color = Sex) +
  geom_line() +
  labs(x="Age (Years)") +
  labs(y="Earnings (USD)") +
* labs(title = "Age vs. Median Earnings by Sex")
```
]
 
.panel2-the_chunk-auto[
<img src="ex2.3_embed_files/figure-html/the_chunk_auto_21_output-1.png" width="576" /><img src="ex2.3_embed_files/figure-html/the_chunk_auto_21_output-2.png" width="576" />
]

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