Update TD5.espec.md

TD5.espec.md

 ## TD5: Data Manipulation with dplyr
 
 Using the [first name data
-set of INSEE](https://www.insee.fr/fr/statistiques/fichier/2540004/dpt2015_txt.zip), answer some of the following questions (you also have to use
+set of INSEE](https://www.insee.fr/fr/statistiques/fichier/2540004/dpt2017_txt.zip), answer some of the following questions (you also have to use
 **ggplot2**):
 
 - First name frequency evolves along time?
@@ -13,24 +13,35 @@ set of INSEE](https://www.insee.fr/fr/statistiques/fichier/2540004/dpt2015_txt.z
 We have demonstrated the use of the six verbs in [our demonstration of
 dplyr](./TD5/TD5.Rmd).
 
-1. Install dplyr and magrittr
+1. Using the [given names data set of INSEE](https://www.insee.fr/fr/statistiques/fichier/2540004/dpt2017_txt.zip), answer some of the following questions:
 
-   ```
-   install.packages("ggplot2");
-   install.packages("magrittr");
-   ```
+- First name frequency evolves along time?
+- What can we say about ``Your name here'' (for each state, all the country)?
+- Is there some sort of geographical correlation with the data?
+- Which department has a larger variety of names along time?
+- _your own question_ (be creative)
 
+You need to use the _tidyverse_ for this analysis. Unzip the file _dpt2016_txt.zip_ (to get the **dpt2017.txt**). Read in R with this code. Note that you might need to install the `readr` package with the appropriate command.
 
+2. Download Raw Data from the website
+```{r}
+file = "dpt2017_txt.zip"
+if(!file.exists(file)){
+  download.file("https://www.insee.fr/fr/statistiques/fichier/2540004/dpt2017_txt.zip",
+	destfile=file)
+}
+unzip(file)
+```
 
-3. Unzip the file _dpt2015_txt.zip_ (to get the **dpt2015.txt**)
+3.  Build the Dataframe from file
 
-4. Read in R with this code. Note that you might need to
-install the `readr` package with the appropriate command.
+```{r}
+library(tidyverse)
+library(ggplot2)
 
-   ```
-   library(readr);
-   df <- read_tsv("dpt2015.txt", locale = locale(encoding = "ISO-8859-1"));
-   ```
+df <- read_tsv("dpt2017.txt", locale = locale(encoding = "ISO-8859-1"));
+df %>% head(n=10)
+```
 
 4. Create your own R markdown (Rmd). Follow the PL guidelines,
 explaining your data manipulation and plot.