How to Use slice() functions to Take Row Slices of Dataframes

# How to Use <em>slice()</em> functions to Take Row Slices of Dataframes
## Selecting Groups and Extremes of Rows
### Peter Higgins
### 2021-01-10

---

### How to Use the _slice()_ functions to Take Row Slices of Dataframes

####

If you want the first 1:N rows, or 50:100 rows, or last 100 rows,
however the dataframe is currently sorted,
you can use variants of the _slice()_ function.

The _slice_max()_ and _slice_min()_ can take rows at top or 
bottom of particular values, using N or proportion.

Let's try some **slicing** examples.

---

```r
# how many rows when you start
*nrow(covid_dates)
```
]
 
.panel2-filter1-auto[

```
[1] 15524
```
]

---
count: false
 
Example 1/4: Slice Rows 100-200
.panel1-filter1-auto[

```r
# how many rows when you start
nrow(covid_dates)

*covid_dates
```
]
 
.panel2-filter1-auto[

```
[1] 15524
```

```
# A tibble: 15,524 x 18
   subject_id fake_first_name fake_last_name gender pan_day test_id clinic_name
        <dbl> <chr>           <chr>          <chr>    <dbl> <chr>   <chr>      
 1       1412 jhezane         westerling     female       4 covid   inpatient …
 2        533 penny           targaryen      female       7 covid   clinical l…
 3       9134 grunt           rivers         male         7 covid   clinical l…
 4       8518 melisandre      swyft          female       8 covid   clinical l…
 5       8967 rolley          karstark       male         8 covid   emergency …
 6      11048 megga           karstark       female       8 covid   oncology d…
 7        663 ithoke          targaryen      male         9 covid   clinical l…
 8       2158 ravella         frey           female       9 covid   emergency …
 9       3794 styr            tyrell         male         9 covid   clinical l…
10       4706 wynafryd        seaworth       male         9 covid   clinical l…
# … with 15,514 more rows, and 11 more variables: result <chr>,
#   demo_group <chr>, age <dbl>, drive_thru_ind <dbl>, ct_result <dbl>,
#   orderset <dbl>, payor_group <chr>, patient_class <chr>, col_rec_tat <dbl>,
#   rec_ver_tat <dbl>, fake_date <date>
```
]

---
count: false
 
Example 1/4: Slice Rows 100-200
.panel1-filter1-auto[

```r
# how many rows when you start
nrow(covid_dates)

covid_dates %>%
# check if all rows distinct
* slice(100:200)
```
]
 
.panel2-filter1-auto[

```
[1] 15524
```

```
# A tibble: 101 x 18
   subject_id fake_first_name fake_last_name gender pan_day test_id clinic_name
        <dbl> <chr>           <chr>          <chr>    <dbl> <chr>   <chr>      
 1        722 joseran         greyjoy        male        12 covid   clinical l…
 2        902 owen            seaworth       male        12 covid   emergency …
 3       1840 jocelyn         tarly          female      12 covid   clinical l…
 4       2025 urswyck         baelish        male        12 covid   ob gyn     
 5       2026 bellonara       snow           female      12 covid   laboratory 
 6       2116 penny           kettleblack    female      12 covid   radiation …
 7       2341 penny           kettleblack    female      12 covid   cc care nt…
 8       2573 glendon         lannister      male        12 covid   emergency …
 9       2859 boros           lannister      male        12 covid   emergency …
10       3781 randa           tyrell         female      12 covid   clinical l…
# … with 91 more rows, and 11 more variables: result <chr>, demo_group <chr>,
#   age <dbl>, drive_thru_ind <dbl>, ct_result <dbl>, orderset <dbl>,
#   payor_group <chr>, patient_class <chr>, col_rec_tat <dbl>,
#   rec_ver_tat <dbl>, fake_date <date>
```
]

---
count: false
 
Example 1/4: Slice Rows 100-200
.panel1-filter1-auto[

```r
# how many rows when you start
nrow(covid_dates)

covid_dates %>%
# check if all rows distinct
  slice(100:200)

# see how many rows now

# Format:
*#   slice(rownum1 : rownum2)                    <br>  #   slice(rownum1 : rownum2)                    <br>
```
]
 
.panel2-filter1-auto[

```
[1] 15524
```

---

count: false
 
Example 2/4: Slice Rows with Top 20 age values
.panel1-filter2-auto[

```r
# how many rows when you start
*nrow(covid_dates)
```
]
 
.panel2-filter2-auto[

```
[1] 15524
```
]

---
count: false
 
Example 2/4: Slice Rows with Top 20 age values
.panel1-filter2-auto[

```r
# how many rows when you start
nrow(covid_dates)

*covid_dates
```
]
 
.panel2-filter2-auto[

```
[1] 15524
```

---
count: false
 
Example 2/4: Slice Rows with Top 20 age values
.panel1-filter2-auto[

```r
# how many rows when you start
nrow(covid_dates)

covid_dates %>%
* select(age, gender, pan_day)
```
]
 
.panel2-filter2-auto[

```
[1] 15524
```

```
# A tibble: 15,524 x 3
     age gender pan_day
   <dbl> <chr>    <dbl>
 1   0   female       4
 2   0   female       7
 3   0.8 male         7
 4   0.8 female       8
 5   0.8 male         8
 6   0.8 female       8
 7   0.8 male         9
 8   0   female       9
 9   0   male         9
10   0.9 male         9
# … with 15,514 more rows
```
]

---
count: false
 
Example 2/4: Slice Rows with Top 20 age values
.panel1-filter2-auto[

```r
# how many rows when you start
nrow(covid_dates)

covid_dates %>%
  select(age, gender, pan_day) %>%
# more than 20 because of ties, auto-sorts
* slice_max(age, n=20)
```
]
 
.panel2-filter2-auto[

```
[1] 15524
```

```
# A tibble: 22 x 3
     age gender pan_day
   <dbl> <chr>    <dbl>
 1   138 female     105
 2   119 female      48
 3   119 male        87
 4   119 female     100
 5   119 female     105
 6    99 female      94
 7    98 female      81
 8    98 male        87
 9    98 male        88
10    98 female      94
# … with 12 more rows
```
]

---
count: false
 
Example 2/4: Slice Rows with Top 20 age values
.panel1-filter2-auto[

```r
# how many rows when you start
nrow(covid_dates)

covid_dates %>%
  select(age, gender, pan_day) %>%
# more than 20 because of ties, auto-sorts
  slice_max(age, n=20)

# see how many rows now

# Format:
*#   slice_max(variable, n = x)                    <br>  #   slice_max(variable, n = x)                    <br>
```
]
 
.panel2-filter2-auto[

```
[1] 15524
```

---

count: false
 
Example 3/4: Slice Rows with Bottom 1% of -Earliest- Pandemic Day
.panel1-filter3-auto[

```r
# how many rows when you start
*nrow(covid_dates)
```
]
 
.panel2-filter3-auto[

```
[1] 15524
```
]

---
count: false
 
Example 3/4: Slice Rows with Bottom 1% of -Earliest- Pandemic Day
.panel1-filter3-auto[

```r
# how many rows when you start
nrow(covid_dates)

*covid_dates
```
]
 
.panel2-filter3-auto[

```
[1] 15524
```

---
count: false
 
Example 3/4: Slice Rows with Bottom 1% of -Earliest- Pandemic Day
.panel1-filter3-auto[

```r
# how many rows when you start
nrow(covid_dates)

covid_dates %>%
* select(age, gender, pan_day)
```
]
 
.panel2-filter3-auto[

```
[1] 15524
```

---
count: false
 
Example 3/4: Slice Rows with Bottom 1% of -Earliest- Pandemic Day
.panel1-filter3-auto[

```r
# how many rows when you start
nrow(covid_dates)

covid_dates %>%
  select(age, gender, pan_day) %>%
* slice_min(pan_day, prop = 0.01)
```
]
 
.panel2-filter3-auto[

```
[1] 15524
```

```
# A tibble: 178 x 3
     age gender pan_day
   <dbl> <chr>    <dbl>
 1   0   female       4
 2   0   female       7
 3   0.8 male         7
 4   0.8 female       8
 5   0.8 male         8
 6   0.8 female       8
 7   0.8 male         9
 8   0   female       9
 9   0   male         9
10   0.9 male         9
# … with 168 more rows
```
]

---
count: false
 
Example 3/4: Slice Rows with Bottom 1% of -Earliest- Pandemic Day
.panel1-filter3-auto[

```r
# how many rows when you start
nrow(covid_dates)

covid_dates %>%
  select(age, gender, pan_day) %>%
  slice_min(pan_day, prop = 0.01)

# see how many rows now

# Format:
*#   slice_min(variable, prop = 0.nn)                    <br>  #   slice_min(variable, prop = 0.nn)                    <br>
```
]
 
.panel2-filter3-auto[

```
[1] 15524
```

---

```r
# how many rows when you start
*nrow(covid_dates)
```
]
 
.panel2-filter4-auto[

```
[1] 15524
```
]

---
count: false
 
Example 4/4: Slice Top or Bottom N or %
.panel1-filter4-auto[

```r
# how many rows when you start
nrow(covid_dates)

*covid_dates
```
]
 
.panel2-filter4-auto[

```
[1] 15524
```

---
count: false
 
Example 4/4: Slice Top or Bottom N or %
.panel1-filter4-auto[

```r
# how many rows when you start
nrow(covid_dates)

covid_dates %>%
* select(age, gender, pan_day)
```
]
 
.panel2-filter4-auto[

```
[1] 15524
```

---
count: false
 
Example 4/4: Slice Top or Bottom N or %
.panel1-filter4-auto[

```r
# how many rows when you start
nrow(covid_dates)

covid_dates %>%
  select(age, gender, pan_day) %>%
* slice_tail(prop = 0.01)
```
]
 
.panel2-filter4-auto[

```
[1] 15524
```

```
# A tibble: 155 x 3
     age gender pan_day
   <dbl> <chr>    <dbl>
 1  40   female     106
 2  17   female     106
 3  17   female     106
 4  17   male       106
 5   0.8 male       106
 6   0.7 male       106
 7  17   female     106
 8   7   male       106
 9  17   male       106
10  71   male       106
# … with 145 more rows
```
]

---
count: false
 
Example 4/4: Slice Top or Bottom N or %
.panel1-filter4-auto[

```r
# how many rows when you start
nrow(covid_dates)

covid_dates %>%
  select(age, gender, pan_day) %>%
  slice_tail(prop = 0.01)

# see how many rows now

# Format:
*#   slice_min(variable, prop = 0.nn)                    <br>  #   slice_min(variable, prop = 0.nn)                    <br>
```
]
 
.panel2-filter4-auto[

```
[1] 15524
```

---
class: inverse, center

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