#httr

[icu-envy-me]

Almost game time!

[karagin22]

[mrbopst]

Monday Night Football: 1971 Washington Redskins vs 1986 New York Giants

[dalydose22]

This week on the Daly Dose, we are hosting our annual NFL preview! We are joined by a few friends of the podcast to break down a number of storylines and make our picks for every division in the league! The Washington Commanders have a new owner, NFL running backs are feeling disrespected, and we look at some coaches that will be on the hot seat to begin the season! We begin with the AFC East. Can the Buffalo Bills overcome some personnel losses to stay on top? Can the Miami Dolphins keep their QB healthy? Will the New England Patriots improve on offense? Can the New York Jets actually live up to all of the hype? In the NFC East, can the Dallas Cowboys live up to expectations? Were the New York Giants a fluke last season? Can the Philadelphia Eagles avoid a Super Bowl hangover? Will the Washington Commanders be better than expected? We move to the AFC North, did the Baltimore Ravens get Lamar Jackson enough help? Can Deshaun Watson rebound for the Cleveland Browns? Will the Cincinnati Bengals keep winning clutch games? Can the Pittsburgh Steelers take another step forward under QB Kenny Pickett? Finally, we reach the NFC North! Are the Chicago Bears going to surprise the league? Can the Detroit Lions break their playoff drought? Are the Green Bay Packers going to be better under Jordan Love? Can the Minnesota Vikings improve on last year’s playoff disappointment? We answer these questions and many more this week on the Dose!

[happy10thousandyears]

Okay they whitewashed both of them but the printing quality is p good 👍 so I’m not gonna complain

[camarajordan]

🔴🟡🔴🟡

💪🏾💪🏾💪🏾💪🏾

[mindrole]

random headcanon of mine that means nothing but i really like anyway:

snmt is absolutely colorblind. its super random, but he probably didn't realize it until he had haruki and rai had to pull him aside because he was teaching him colors all wrong

also face blind honestly

[tea-and-secrets]

Dude. My gucking

Asshole httrs

I have shat five tiems today all the time my poopoo has been soft and smoith but it hurs bax

Hemoriods

I thiabj I may have them or what rhwurte they called thagain

Anak fishers

Wh does i hurt if poopoo soft??? Help me im ucking dying

The tiles gripping jot helping m y body is cold and shaking and shiveirng ehy does it feel cold when its fucking 90 degtes how

.

[ariapmdeol]

do seodore coe :3

How I feel about this character:

🫶 I like that guy!!! I like seodore!! I get so excited when characters have plans and by god does seodore have plans. I love the different ways that characters think about Gods Love and the different plans revolving around it, and I really really like that Seodore has his own feelings about it. I’m a big fan of metafiction and the dynamics surrounding different levels of meta-awareness! I really like his message to YoUser at the end of DLC and I love his purple text guiding us towards the Empyrean point!! The character is aware of the narrative and that’s so much fun!!!

A lot of seodore stuff is so fun because he implies so much shit. So much of my theory brainrot is because he just Says So Much and Implies Lore Things and it’s so fun!!

Lately I’ve been thinking a lot about Theodore Riddle (pre-shipwreck) vs Seodore Riddle (post-shipwreck)… we know nothing abt Theodore but I have thoughts either way.

All the people I ship romantically with this character:

Woah hey guys I wonder what ships I’ll li—

Sanemitsu!!! This is peak yaoi to me. I’ve spoken on them extensively before but there’s something so compelling about those two!!! Their different POVs on how to handle the narrative, on what to do with Gods Love… it makes me so crazy because they understand each other, and understand why the other makes the decisions that they do. It’s about all the things left unspoken but they both know already. Killing Seodore for the chance to try to save Reiji. Dying together and killing those versions of themselves for the chance at a better ending. The way Seodore opens his eyes for one frame when Snmt kills him. The Holding hands. I like those guys a lot. I already wrote an essay on this but they live in my head rent free. They should hold hands again.

Rumeld! Ok this is also an obvious one but they’re cute!!! I like how comfortable they are with each other. Their chapter in Interlude is SO adorable and I think it’s sweet that Seo is still so in love with Rumeld, after all this time. Date day is soon, too… I’ll need to draw something for them.

This isn’t quite a ship but I think Dreyseo is neat in a “just sex” way. It implies that Seo has A Type which is REALLY funny.

My non-romantic OTP for this character:

I’m not picking just one so we get a whole bunch of groups here

Ok this is more of a grouping but I really like the group dynamics at play between System.NH + Seodore + Mutei! They all have different ideas on what to do with Gods Love and the world that they live in, and it’s really compelling to me!

LDL as a group is also really good!!! Really really good!!! I just really like that they all know that the others have their own goals in all of this, and choose to work together. I like the coordination. I also really like Seo and Reiji’s dynamic.. everyone working together to raise Reiji and through the power of teamwork, they manage to be good parents LAHDDKHJF. I love how Seodore is great with anyone not related to him (you see this with Reiji and Noa) but then with Hatsutori, he’s not great KAGEKRHRJRH

Connected to this: FRAGMENTS! I think httr+seo are so good! Bird parent and child! Fucked up!!!! Seo was not the parental figure that httr needed and their complicated feelings for each other makes me crazy. The animosity is so so good!!!

My unpopular opinion about this character:

im gonna be honest. i think a lot of people dont understand him. i disagree with the idea that he's aggressive? we see him bicker with httr, yeah, but httr is fighting just as hard. the only time we see him actually lose his temper is in record 5, and hajime had already been pushing deiberately to antagonize him. i dont think we can use "had his emotional weak spots targeted until he snapped" as "typical seodore reactions". those are special circumstances all around.

i think there are have been many times where I've read takes on seodore and i've disagreed... I think because he’s not really there until late DLC, people get really confused about him. I don’t know if this is a popular or unpopular opinion, though.

One thing I wish would happen/had happened with this character in canon:

PLEASE ryu-seo conversation… i want ryu to meet his mom… it would be funny…

i also would love a seo-izu-snmt conversation.. izu is technically the seosane lovechild if you think about i—- *i am removed from tumblr dot com*

[icu-envy-me]

[karagin22]

[mrbopst]

October 19, 1969 - Washington Redskins linebacker Sam Huff waits for the snap during a 20-14 victory over the New York Giants at RFK Stadium.

[gloriousfestgentlemen02]

Sure, here is a 500-word article on "SEO automation with R" as per your request:

SEO Automation with R TG@yuantou2048

Search Engine Optimization (SEO) is a critical aspect of digital marketing that helps websites rank higher in search engine results pages (SERPs). Traditionally, SEO tasks have been manual and time-consuming, but with the advent of advanced programming languages like R, many of these tasks can now be automated using R.

Why Use R for SEO Automation?

R is a powerful statistical programming language that offers a wide range of packages specifically designed for data manipulation, analysis, and visualization. Here are some reasons why R is an excellent choice for automating SEO tasks:

1. Data Handling: R excels at handling large datasets, which is crucial for SEO where you often need to analyze vast amounts of data from various sources such as Google Analytics, SEMrush, Ahrefs, etc.

2. Automation: With R, you can automate repetitive tasks such as keyword research, backlink analysis, and content optimization. This not only saves time but also reduces the risk of human error.

3. Customization: R allows for high customization, enabling you to tailor solutions to specific needs. You can create custom scripts to scrape data from different sources, perform complex calculations, and generate reports automatically.

4. Integration: R integrates well with other tools and platforms. You can easily connect to APIs from tools like Google Search Console, Moz, and others, making it easier to gather and process data efficiently.

5. Visualization: R has robust visualization capabilities, allowing you to create insightful visual representations of your SEO data, helping you make informed decisions based on data-driven insights.

6. Community Support: The R community is vast and active, providing extensive support through packages like `httr` for web scraping, `dplyr` for data manipulation, and `ggplot2` for creating detailed visualizations that help in understanding trends and patterns in your SEO metrics.

Steps to Automate SEO Tasks

Step 1: Data Collection

Use packages like `httr` and `rvest` to scrape data from websites and APIs. For example, you can use `httr` to fetch data from APIs and `rvest` to extract data from HTML documents. This makes it easy to collect and clean data from multiple sources.

Example: Keyword Research

```r

library(httr)

library(rvest)

Fetching data from a website

url <- "https://example.com"

page <- GET(url)

content <- read_html(page)

keywords <- html_nodes(content, "h1") %>% html_text()

print(keywords)

```

This snippet demonstrates how to scrape keywords from a webpage. By leveraging these packages, you can automate the collection of data from SEO tools and websites.

Step-by-Step Guide

1. Install Required Packages

```r

install.packages("httr")

install.packages("rvest")

```

2. Scrape Data

```r

url <- "https://example.com"

page <- read_html(url)

titles <- html_nodes(page, "h1") %>% html_text()

print(titles)

```

3. Data Analysis

```r

library(dplyr)

library(ggplot2)

Example: Extracting H1 tags from a webpage

url <- "https://example.com"

page <- read_html(url)

h1_tags <- html_nodes(page, "h1") %>% html_text()

print(h1_tags)

```

4. Data Manipulation

```r

library(dplyr)

library(stringr)

library(tidyr)

Scrape data

url <- "https://example.com"

page <- read_html(url)

titles <- html_nodes(page, "h1") %>% html_text()

```

5. Data Cleaning and Analysis

```r

df <- data.frame(titles = titles)

df <- df %>% mutate(word_count = str_length(titles))

```

6. Analysis

```r

df <- df %>% mutate(word_count = str_length(titles))

```

7. Visualization

```r

library(ggplot2)

ggplot(df, aes(x = titles)) +

geom_bar() +

labs(title = "Keyword Frequency", x = "Keywords", y = "Frequency")

Analyze and visualize data

df <- df %>% group_by(titles) %>%

summarize(count = n())

```

8. Visualization

```r

ggplot(df, aes(x = titles, y = count)) +

geom_bar(stat = "identity")

```

9. Reporting

```r

ggplot(df, aes(x = titles, y = count)) +

geom_bar(stat = "identity")

```

10. Conclusion

By automating these tasks, you can streamline your SEO workflow, saving hours of manual labor.

11. Automated Reports

```r

ggplot(df, aes(x = titles, y = count)) +

theme_minimal()

ggplot(df, aes(x = titles, y = count)) +

geom_bar(stat = "identity")

```

12. Automate Reporting

```r

ggsave("report.png")

```

13. Conclusion

By automating SEO tasks with R, you can focus more on strategic decisions rather than spending time on mundane tasks. This approach ensures consistency and accuracy in your SEO efforts, leading to better insights and faster decision-making.

14. Summary

In conclusion, automating SEO tasks with R can significantly enhance your SEO strategy by providing actionable insights quickly and efficiently. Whether you're a beginner or an experienced SEO professional, integrating R into your workflow can transform your SEO strategy, making it more efficient and effective. Start exploring R today to elevate your SEO efforts and stay ahead in the competitive digital landscape.

15. Final Thoughts

Automating SEO processes with R empowers marketers to focus on strategic planning and execution, ultimately driving better rankings and improving overall performance.

16. Next Steps

Explore more packages like `shiny` for interactive dashboards or `shiny` for interactive dashboards and reports.

17. TG@yuantou2048

```

By leveraging R, you can save time and gain deeper insights into your website's performance and make data-driven decisions.

18. TG@yuantou2048

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Feel free to reach out if you need further assistance or have any questions!

加飞机@yuantou2048

EPS Machine

EPP Machine

[lysun-reminder]

Data import and export in R

R is a versatile tool that can handle a wide range of data sources, making it a go-to language for data analysis and statistical computing. Whether you’re working with CSV files, Excel spreadsheets, or databases, R provides powerful functions and packages to import and export data efficiently. In this section, we’ll explore how to import data from various sources and export your results back into different formats.

Importing Data from CSV Files

CSV (Comma-Separated Values) is one of the most common formats for storing and exchanging data. R has built-in functions to read and write CSV files, making it easy to import data for analysis.

Using read.csv():

The read.csv() function is used to read data from a CSV file into a data frame.# Importing a CSV file data <- read.csv("path/to/your/file.csv") # Display the first few rows of the data head(data)

Customizing the Import:

You can customize how the data is imported by using additional arguments such as header, sep, and stringsAsFactors.# Importing a CSV file with custom settings data <- read.csv("path/to/your/file.csv", header = TRUE, sep = ",", stringsAsFactors = FALSE)

header = TRUE: Indicates that the first row contains column names.

sep = ",": Specifies the separator used in the CSV file.

stringsAsFactors = FALSE: Prevents character strings from being converted into factors.

Importing Data from Excel Files

Excel is another widely used format for storing data, especially in business environments. R provides several packages to read and write Excel files, with readxl and openxlsx being two popular options.

Using readxl Package:

The readxl package allows you to read Excel files without needing to install external dependencies.# Install and load the readxl package install.packages("readxl") library(readxl) # Importing an Excel file data <- read_excel("path/to/your/file.xlsx", sheet = 1) # Display the first few rows of the data head(data)

sheet = 1: Specifies which sheet to read from the Excel file.

Using openxlsx Package:

The openxlsx package offers more flexibility, including writing data back to Excel files.# Install and load the openxlsx package install.packages("openxlsx") library(openxlsx) # Importing an Excel file data <- read.xlsx("path/to/your/file.xlsx", sheet = 1) # Display the first few rows of the data head(data)

Importing Data from Databases

R can also connect to various databases, allowing you to import large datasets directly into R. The DBI package is a standard interface for communication between R and databases, and it works with several backend packages like RMySQL, RPostgreSQL, and RSQLite.

Using DBI and RSQLite:

Here’s an example of how to connect to a SQLite database and import data.# Install and load the DBI and RSQLite packages install.packages("DBI") install.packages("RSQLite") library(DBI) library(RSQLite) # Connect to a SQLite database con <- dbConnect(RSQLite::SQLite(), dbname = "path/to/your/database.sqlite") # Importing a table from the database data <- dbGetQuery(con, "SELECT * FROM your_table_name") # Display the first few rows of the data head(data) # Disconnect from the database dbDisconnect(con)

Connecting to Other Databases:

Similar procedures apply when connecting to MySQL, PostgreSQL, or other databases, with the appropriate backend package (RMySQL, RPostgreSQL, etc.).

Importing Data from Other Sources

R supports data import from various other sources such as: JSON: Using the jsonlite package.

XML: Using the XML or xml2 packages.

Web Data: Using the httr or rvest packages to scrape data from websites.

SPSS, SAS, Stata: Using the haven package to import data from statistical software.

Here’s an example of importing JSON data:# Install and load the jsonlite package install.packages("jsonlite") library(jsonlite) # Importing a JSON file data <- fromJSON("path/to/your/file.json") # Display the first few rows of the data head(data)

Exporting Data from R

Once you’ve processed or analyzed your data in R, you may want to export it for reporting, sharing, or further use.

Exporting to CSV:

The write.csv() function allows you to export data frames to a CSV file.# Exporting data to a CSV file write.csv(data, "path/to/save/your/file.csv", row.names = FALSE)

row.names = FALSE: Prevents row names from being written to the file.

Exporting to Excel:

If you used the openxlsx package, you can also write data frames to Excel files.# Exporting data to an Excel file write.xlsx(data, "path/to/save/your/file.xlsx")

Exporting to Databases:

You can use the dbWriteTable() function from the DBI package to export data back into a database.# Connecting to the database con <- dbConnect(RSQLite::SQLite(), dbname = "path/to/your/database.sqlite") # Writing data to a new table in the database dbWriteTable(con, "new_table_name", data) # Disconnecting from the database dbDisconnect(con)

Best Practices for Data Import and Export

Data Validation: Always inspect the first few rows of your imported data using head() to ensure it has been read correctly.

Customizing Imports: Use the various arguments available in the import functions to handle specific file structures or formatting issues.

Keep a Clean Workspace: After importing and exporting data, clean up your workspace by removing temporary objects or closing database connections to prevent memory issues.

Full details available at https://strategicleap.blogspot.com/

[sports-brew]

NFL Playoffs, Redskins Upset Lions, Bills, Ravens Get Cute, Chiefs Officiating blowback, Terry McLaurin, JD5 Dap, the ELGSES, Karmic FU for Dan Snyder, Ichiro HoF Vote, HTTR Dedication RIP 01-23-2025

[papi1973]

At work but ready for some football. Let’s go Washington HTTR