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esm244_reprex_practice's Issues

Coloring points by name - Shuying Yu

Cool plot

library(reprex)
library(tidyverse)

#Dataframe
df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

#Create graph
ggplot(data = df, aes(x = wt, y = ht)) +
  
  #Color point by name
  geom_point(aes(color = name))

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Terrible penguin graph, why won't my color work for year?? why is my facet_wrap not working? why is it breaking after that?? - Trevor Maggart

library(tidyverse)
library(palmerpenguins)

ggplot(penguins, aes(x = body_mass_g, y = flipper_length_mm)) +
         geom_point(color = year) +
         facet_wrap(~'species') 
#> Error in layer(data = data, mapping = mapping, stat = stat, geom = GeomPoint, : object 'year' not found
         theme_classic()
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^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Why is my graph not working?! Plz help - Taylor Gries

library(tidyverse)
library(palmerpenguins)

ggplot(penguins, aes(x = flipper_length_mm, y = body_mass_g)) +
  geom_pt(aes(color = species)) +
  facet_wrap(~ year) +
  theme_minimal()
#> Error in geom_pt(aes(color = species)): could not find function "geom_pt"

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Been stuck since 2021, please help! - Tiffany Hsu

I just can't seem to figure this one out...

library(tidyverse)
library(palmerpenguins)

penguins_subset<- penguins %>% 
  select(species, body_mass_g, flipper_length_mm) %>% 
  summarize(mean_mass_g = mean(body_mass))
#> Error: Problem with `summarise()` input `mean_mass_g`.
#> x object 'body_mass' not found
#> ℹ Input `mean_mass_g` is `mean(body_mass)`.

^{Created on 2022-01-04 by the reprex package (v0.3.0)}

Look at this cool plot! - Sophia Leiker

library(tidyverse)

df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

ggplot(data = df, aes(x = name, y =wt)) +
  geom_point(aes(color = wt))

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Discussion 1: Working Example Graph (German Silva)

A success!

library(tidyverse)

df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

ggplot(data = df, aes(x= ht, y = wt)) +
  geom_point() +
  geom_smooth(method = "lm")
#> `geom_smooth()` using formula 'y ~ x'

^{Created on 2022-01-06 by the reprex package (v2.0.1)}

my friends :') - Trevor Maggart

library(tidyverse)
library(datapasta)

my_friends <- tibble::tribble(~name, ~eye_color, ~height,
                              "Rhea", "green", 180,
                              "Nathaniel","blue", 186,
                              "Shayan", "brown", 175,
                              "Shaylin", "brown", 168)

my_friends %>%
  group_by(eye_color) %>%
  summarize(mean_ht = mean(height))
#> # A tibble: 3 × 2
#>   eye_color mean_ht
#>   <chr>       <dbl>
#> 1 blue         186 
#> 2 brown        172.
#> 3 green        180

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

This graph works and is ugly (Joseph Kilgallen)

library(tidyverse)
library(reprex)


df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

ggplot(data = df, aes(x = wt, y =ht)) +
  geom_point(color ='blue') +
  theme_minimal() +
  labs(x= "Weight", y= "Height", title =  "Boring plot")

^{Created on 2022-01-06 by the reprex package (v2.0.1)}

Penguins Issue, can't find Gentoo! - Sam Kuglen

library(tidyverse)
library(palmerpenguins)

female_penguins <- penguins %>% 
  filter(species = "Gentoo") %>% 
  group_by(species) 
#> Error: Problem with `filter()` input `..1`.
#> x Input `..1` is named.
#> ℹ This usually means that you've used `=` instead of `==`.
#> ℹ Did you mean `species == "Gentoo"`?

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Why can't I print the mean value for Adelie and Gentoo?(Narjes Mathlouthi)

library(tidyverse)
library(palmerpenguins)

penguins %>%
  group_by(species) %>%
  summarize(mean = mean(bill_length_mm, na.rm = FALSE))
#> # A tibble: 3 × 2
#>   species    mean
#>   <fct>     <dbl>
#> 1 Adelie     NA  
#> 2 Chinstrap  48.8
#> 3 Gentoo     NA

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

thing

why no work?!

library(tidyverse)
library(palmerpenguins)

penguins %>%
  group_by(species) %>%
  summarize(mean_wt = mean(body_mass_g))
#> # A tibble: 3 × 2
#>   species   mean_wt
#>   <fct>       <dbl>
#> 1 Adelie        NA 
#> 2 Chinstrap   3733.
#> 3 Gentoo        NA
ggplot(penguins, aes(x = flipper_length_mm, y = body_mass_g)) +
  geom_point(aes(color = 'species')) +
  scale_color_viridis_d() +
  theme_classic()
#> Warning: Removed 2 rows containing missing values (geom_point).

^{Created on 2022-01-01 by the reprex package (v2.0.1)}

Pesky penguins - Erika Egg

What is the issue in grouping?

library(tidyverse)
library(palmerpenguins)

fem_peng_grouped <- penguins %>% 
  filter(sex == "female") %>% 
  group_by(~species)
#> Error: Problem adding computed columns in `group_by()`.
#> x Problem with `mutate()` input `..1`.
#> ℹ `..1 = ~species`.
#> x `..1` must be a vector, not a `formula` object.

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Number of species across land-use changes (Kacie Ring)

#Submit a working reprex example as a github issue 

#Step 1: call in the tidyverse
library(tidyverse)
library(ggplot2)
#Step 2 : make a tibble with a tribble 

df <- tribble(~land_use, ~size_ha, ~species, ~invasive_species, ~native_species,
              "primary_forest", 15, 42, 15, 27,
              "secondary_forest", 8, 36, 16, 20,
              "agriculture", 4, 25, 20, 5,
              "urban", 6, 9, 7, 2)


#Step 2: Write some code that successfully creates a graph or a summary statistic
graph <-ggplot(df, aes(y=species, x=land_use, fill = land_use)) +
    geom_bar(stat="identity")+theme_minimal() 

graph2 <- graph + theme(axis.text.x = element_text(angle = 90)) 

graph2 + ggtitle("Number of species along a land-use gradient") +
  xlab("Land use type") + ylab("Number of species (count)")

^{Created on 2022-01-06 by the reprex package (v2.0.1)}

Dog weight summary stats (Kort Alexander)

library(tidyverse)

df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

stats <- df %>% 
  group_by() %>% 
  summarize(mean_wt = mean(wt), sd_wt = sd(wt))

^{Created on 2022-01-06 by the reprex package (v2.0.1)}

Error with summary statistics - Katie Munster

library(tidyverse)
library(palmerpenguins)

penguins %>%
  group_by(islands) %>% 
  summarize(mean_bill_length = mean(bill_length_mm))
#> Error: Must group by variables found in `.data`.
#> * Column `islands` is not found.

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

lab1 - working example - basic graph (Chelsie McWhorter)

library(tidyverse)

df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

df_graph <- ggplot(data = df, aes(x = wt, y = ht)) +
  geom_col()

^{Created on 2022-01-06 by the reprex package (v2.0.1)}

How can I be less basic?

library(tidyverse)

# make a tibble with tribble:
df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

# create a graph or summary statistic
ggplot(data = df, 
       aes(x = wt, y = ht)) +
  geom_point()

3 Pups Summary Statistics - Sarah Lam

library(tidyverse)

df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

dog_summary <- df %>% 
  summarize(mean_weight = mean(wt), 
            sd_weight = sd(ht),
            mean_height = mean(ht), 
            sd_hegith = sd(ht))

dog_summary
#> # A tibble: 1 × 4
#>   mean_weight sd_weight mean_height sd_hegith
#>         <dbl>     <dbl>       <dbl>     <dbl>
#> 1        46.7       0.1         0.5       0.1

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

california population data? - Taylor Medina

library(tidyverse)

ca_county <- tribble(
  ~county, ~population, ~density,
  "Los Angeles", 10e6, 2099,
  "San Diego", 3.3e6, 703.4,
  "Orange", 3.1e6, 3255.4)

ca_county_stats <- ca_county %>% 
  group_by() %>% 
  summarize(mean_pop = mean(population))

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Unable to make subset for female adelie penguins?? - Sarah Lam

library(tidyverse)
library(palmerpenguins)

female_adelie <- penguins %>% 
  select(species = "Adelie", sex = "female")
#> Error: Can't subset columns that don't exist.
#> x Column `Adelie` doesn't exist.

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

How do I make my sad graph look more visually pleasing? (Taylor Gries)

library(tidyverse)

df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

ggplot(df, aes(x = name, y = ht)) +
  geom_point()

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

A plot about dogs!- Janelle Gaun

Any witty thoughts about this plot about dogs?

library(tidyverse)
library(ggplot2)

dataframe <- tribble(~name, ~wt, ~ht, 
                    "Teddy", 52, 0.5, 
                    "Khora", 60, 0.6,
                    "Waffle", 28, 0.4)

ggplot(dataframe)+
  geom_point(aes(x = wt, y= ht))

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

It's a Pawty - Tiffany Hsu

Check out the weight distribution of the pups!

library(tidyverse)

df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

ggplot(df, aes(x = name, y = wt)) +
  geom_point() +
  labs(x = "Name",
       y = "Weight") +
  theme_minimal()

^{Created on 2022-01-04 by the reprex package (v0.3.0)}

Dog plot - Mia Guarnieri

library(tidyverse)
# Make a data table with tribble
df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

ggplot(df, aes(x = name, y = wt)) +
  geom_point(color = "blue") +
  labs(x = "Dog", 
       y = "Weight")

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Code won't run, HELP!!!! - Lucas Boyd

library(tidyverse)
library(palmerpenguins)
library(datasets)
library(ggbeeswarm)

ggplot(data = penguins, aes(x = species, y = flipper_length_mm, color = species)) +
  geom_beeswarm() +
  scale_color_manual(values = c("firebrick", "cyan4", "forestgreen")) +
  labs(x = "Species", y = "Flipper Length (mm)") +
  theme(legend.position = "none") %>% 
  theme_minimal()
#> Error in base_size/2: non-numeric argument to binary operator

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Look at this colorful plot!! (Kiera Matiska)

Awesome!

library(tidyverse)

dogs <- tibble::tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

ggplot(dogs, aes(x = name, y = wt)) +
  geom_col(aes(fill = name))

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

what about this awesome plot - Casey O'Hara

cool

library(tidyverse)

penguins_subset <- tibble::tribble(
  ~species, ~body_mass_g, ~flipper_length_mm,
  "Adelie",        3750L,               181L,
  "Adelie",        3800L,               186L,
  "Adelie",        3250L,               195L,
  "Adelie",           NA,                 NA,
  "Adelie",        3450L,               193L,
  "Adelie",        3650L,               190L
  )

ggplot(penguins_subset, aes(x = body_mass_g, y = flipper_length_mm)) +
  geom_point(aes(color = species))
#> Warning: Removed 1 rows containing missing values (geom_point).

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Why am I getting NAs?? (Kiera Matiska)

library(tidyverse)
library(palmerpenguins)

penguins %>% 
  group_by(species) %>% 
  summarize(mean_mm = mean(flipper_length_mm))
#> # A tibble: 3 × 2
#>   species   mean_mm
#>   <fct>       <dbl>
#> 1 Adelie        NA 
#> 2 Chinstrap    196.
#> 3 Gentoo        NA

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

why doesn't my filter work? - Mari Herbst de Cortina

library(tidyverse)
library(palmerpenguins)

penguins_subset <- penguins %>%
  filter(species == "adelie")
#> Error: object 'species' not found

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

How can I make this graph easier to interpret? (Sarah Hamilton)

library(tidyverse)
library(palmerpenguins)

df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

ggplot(data = df, aes(x = ht, y = wt)) +
  geom_point(color = 'darkblue') +
  theme_minimal() +
  labs(x = "height", y = "weight")

^{Created on 2022-01-06 by the reprex package (v2.0.1)}

Why won't my graph work? (Sarah Hamilton)

library(tidyverse)
library(palmerpenguins)

penguins_df <- penguins %>%
  select(bill_length_mm, body_mass_g)

ggplot(data = penguins_df, aes(x = bill_length_mm, y = body_mass_g)) +
  geom_histogram()
#> Error: stat_bin() can only have an x or y aesthetic.

^{Created on 2022-01-06 by the reprex package (v2.0.1)}

graph of cute dawgs - Mari Herbst de Cortina

library(tidyverse)

df <- tribble(~name, ~wt, ~ht,
             "Teddy", 52, 0.5,
             "Khora", 60, 0.6,
             "Waffle", 28, 0.4)

ggplot(data = df, aes(x = wt, y = ht)) +
  geom_point(aes(color = name))

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Graph of dog weights - Katie Munster

library(tidyverse)

df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

ggplot(df, aes(x = name, y = wt)) +
  geom_point() +
  theme_classic()

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

This Code Doesn't Work (Mae Rennick)

library(tidyverse)
library(palmerpenguins)

penguins<- penguins %>% 
  filter(-bill_depth_mm) %>% 
  mutate(sum(species))
#> Error: Problem with `filter()` input `..1`.
#> ℹ Input `..1` is `-bill_depth_mm`.
#> x Input `..1` must be a logical vector, not a double.

^{Created on 2022-01-06 by the reprex package (v2.0.1)}

How can I make this graph better? (Allie Caughman)

library(tidyverse)

df = tribble(~name, ~wt, ~ht,
             "Teddy", 52, 0.5,
             "Khora", 60, 0.6,
             "Waffle", 28, 0.4)

ggplot(data = df, aes(wt, ht)) +
  geom_col() +
  theme_bw() +
  labs(x = "weight",
       y = "height")

^{Created on 2022-01-05 by the reprex package (v2.0.1)}

Dog weights! - Sam Kuglen

library(tidyverse)

df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

ggplot(df, aes(x = name, y = wt)) +
  geom_point(aes(color = name))

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Why can't I select 'species' in palmerpenguin? - Janelle Gaun

I'm trying to select a subset of only Gentoo pengiuns. The data shows a column named 'species'. Why won't it recognize the column name?

library(tidyverse)
library(palmerpenguins)

penguins %>% 
  count(species)
#> # A tibble: 3 x 2
#>   species       n
#>   <fct>     <int>
#> 1 Adelie      152
#> 2 Chinstrap    68
#> 3 Gentoo      124

sub_penguins <- penguins %>% 
  select(species == 'Gentoo')
#> Error: object 'species' not found

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Dog weights (Mae Rennick) Reprex example

library(tidyverse)
  
df <- tribble(~name, ~wt, ~ht,
                "Teddy", 52, 0.5,
                "Khora", 60, 0.6,
                "Waffle", 28, 0.4,
              "Fergus", 56, 0.5)
ggplot(df,aes(x=wt, y=ht))+
  geom_point(aes(color=name))+
  theme_minimal()+
  labs(x="weight(lbs)",
       y="height (meters)")

^{Created on 2022-01-06 by the reprex package (v2.0.1)}

I just want to see penguins by island! (Broken Code)- Sophia Leiker

library(tidyverse)
library(palmerpenguins)

#Working to only retain the species, island, bill_length_mm column
penguins_filtered <- penguins %>%
  filter(species, island,, "bill_length_mm")
#> Error: Problem with `filter()` input `..1`.
#> ℹ Input `..1` is `species`.
#> x Input `..1` must be a logical vector, not a factor<b22a0>.
head(penguins_filtered)
#> Error in head(penguins_filtered): object 'penguins_filtered' not found

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Pup heights - Erika Egg

Check out the heights of these dogs! How could I make it prettier/improve it?

library(tidyverse)

df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

ggplot(df, aes(x = name, y = ht)) +
   geom_point() +
   theme_minimal()

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Super boring working code (Logan Ossentjuk)

library(tidyverse)

ggplot(cars, aes( x = speed, y = dist)) +
  geom_point() +
  theme_classic()

^{Created on 2022-01-06 by the reprex package (v2.0.1)}

Code doesn't break but won't graph sex by color and facet wrap by year?

library(tidyverse)
library(palmerpenguins)

ggplot(data = penguins,
       aes(x = body_mass_g, y = bill_length_mm)) +
  geom_point(aes(color = "sex")) +
  theme_minimal() +
  facet_wrap(~"year")
#> Warning: Removed 2 rows containing missing values (geom_point).

Warning message about removed rows? (Narjes Mathlouthi)

library(tidyverse)


#plot(airquality)
View(airquality)

airquality1 <- tribble(~ozone, ~solar_r, ~temp,
                       20, 120, 55,
                       10, 100, 10,
                       30, 80, 5,)

ggplot(airquality, aes(x = Ozone, y = Solar.R, color = Temp)) +
  geom_jitter() 
#> Warning: Removed 42 rows containing missing values (geom_point).

airquality %>%
  group_by(Temp) %>%
  summarize(mean = mean(Ozone, na.rm = TRUE))
#> # A tibble: 40 × 2
#>     Temp  mean
#>    <int> <dbl>
#>  1    56 NaN  
#>  2    57   6  
#>  3    58  18  
#>  4    59  10  
#>  5    61  14.7
#>  6    62  14.5
#>  7    63  14  
#>  8    64  13.5
#>  9    65  21.5
#> 10    66  24.3
#> # … with 30 more rows

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Penguins issue, island not found - Shuying Yu

Issue for part 4

library(tidyverse)
library(palmerpenguins)

penguins %>% group_by(species) %>% 
  filter(island == Torgersen) %>% 
  summarize(mean_flipper_length_mm = mean(flipper_length_mm))
#> Error: Problem with `filter()` input `..1`.
#> i Input `..1` is `island == Torgersen`.
#> x object 'Torgersen' not found
#> i The error occurred in group 1: species = Adelie.

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Missing flipper length mean and standard deviation on palmer penguins - Taylor Medina

library(tidyverse)
library(palmerpenguins)
#> Warning: package 'palmerpenguins' was built under R version 4.1.2
penguins_subset <- penguins %>% 
  group_by(species) %>% 
  summarize(mean_length = mean(flipper_length_mm),
            sd_length = sd(flipper_length_mm)) 
  
head(penguins_subset)
#> # A tibble: 3 x 3
#>   species   mean_length sd_length
#>   <fct>           <dbl>     <dbl>
#> 1 Adelie            NA      NA   
#> 2 Chinstrap        196.      7.13
#> 3 Gentoo            NA      NA

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Look at these penguins!!! - Lucas Boyd

library(tidyverse)
library(palmerpenguins)
library(datasets)
library(ggbeeswarm)

ggplot(data = penguins, aes(x = species, y = flipper_length_mm, color = species)) +
  geom_beeswarm() +
  scale_color_manual(values = c("firebrick", "cyan4", "forestgreen")) +
  labs(x = "Species", y = "Flipper Length (mm)") +
  theme(legend.position = "none")
#> Warning: Removed 2 rows containing missing values (position_beeswarm).

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Filter not working for female penguins - Mia Guarnieri

library(tidyverse)
library(palmerpenguins)

# Incorrectly wrangling data
female_penguins <- penguins %>% 
  filter(sex = female)
#> Error: Problem with `filter()` input `..1`.
#> x Input `..1` is named.
#> ℹ This usually means that you've used `=` instead of `==`.
#> ℹ Did you mean `sex == female`?

^{Created on 2022-01-04 by the reprex package (v2.0.1)}

Simple graph with names and height - Erin de Leon Sanchez

library(tidyverse)

df <- tribble(~name, ~wt, ~ht,
              "Teddy", 52, 0.5,
              "Khora", 60, 0.6,
              "Waffle", 28, 0.4)

ggplot(df, aes(x = name, y = ht)) +
  geom_col()

^{Created on 2022-01-06 by the reprex package (v2.0.1)}

whyyyyyy (Casey O'Hara)

Why no colors?

library(tidyverse)
library(palmerpenguins)

ggplot(penguins, aes(x = flipper_length_mm, y = body_mass_g)) +
  geom_point(aes(color = 'species'))
#> Warning: Removed 2 rows containing missing values (geom_point).

^{Created on 2022-01-06 by the reprex package (v2.0.1)}

Why doesn't this code get all instances of island I want? (Allie Caughman)

library(tidyverse)
library(palmerpenguins)

penguins_filtered = penguins %>% 
  filter(island == c("Biscoe", "Dream"))

^{Created on 2022-01-05 by the reprex package (v2.0.1)}

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