This is the documentation of the data from [[https://ns.sentiweb.fr/incidence/csv-schema-v1.json][the download site]]:
This is the documentation of the data from [[https://ns.sentiweb.fr/incidence/csv-schema-v1.json][the download site]]:
| Column name | Description |
| Column name | Description |
...
@@ -65,10 +68,12 @@ The [[https://en.wikipedia.org/wiki/ISO_8601][ISO-8601]] format is popular in Eu
...
@@ -65,10 +68,12 @@ The [[https://en.wikipedia.org/wiki/ISO_8601][ISO-8601]] format is popular in Eu
** Download
** Download
After downloading the raw data, we extract the part we are interested in. We first split the file into lines, of which we discard the first one that contains a comment. We then split the remaining lines into columns.
After downloading the raw data, we extract the part we are interested in. We first split the file into lines, of which we discard the first one that contains a comment. We then split the remaining lines into columns.
@@ -79,6 +84,8 @@ Let's have a look at what we have so far:
...
@@ -79,6 +84,8 @@ Let's have a look at what we have so far:
table[:5]
table[:5]
#+END_SRC
#+END_SRC
#+RESULTS:
** Checking for missing data
** Checking for missing data
Unfortunately there are many ways to indicate the absence of a data value in a dataset. Here we check for a common one: empty fields. For completeness, we should also look for non-numerical data in numerical columns. We don't do this here, but checks in later processing steps would catch such anomalies.
Unfortunately there are many ways to indicate the absence of a data value in a dataset. Here we check for a common one: empty fields. For completeness, we should also look for non-numerical data in numerical columns. We don't do this here, but checks in later processing steps would catch such anomalies.