differences for PR #591

05-merging-data.md

@@ -125,7 +125,7 @@ have been repeated. We can reindex the new DataFrame using the `reset_index()` m
 
 ### Writing Out Data to CSV
 
-We can use the `to_csv` command to do export a DataFrame in CSV format. Note that the code
+We can use the `to_csv` command to export a DataFrame in CSV format. Note that the code
 below will by default save the data into the current working directory. We can
 save it to a different folder by adding the foldername and a slash to the file
 `vertical_stack.to_csv('foldername/out.csv')`. We use the `index=False` so that

07-visualization-ggplot-python.md

@@ -232,7 +232,7 @@ to the color aesthetic:
 )
 ```
 
-![](fig/06_color_plot.png){alt='scatter plot of Hindfoot length vs weight with colors coordinating to specfic species, showing abundance in the mid to lower left side of the plot'}
+![](fig/06_color_plot.png){alt='scatter plot of Hindfoot length vs weight with colors coordinating to specific species, showing abundance in the mid to lower left side of the plot'}
 
 Apart from the adaptations of the arguments and settings of the `data`, `aes`
 and `geom-*` elements, additional elements can be added as well, using the `+`
@@ -248,7 +248,7 @@ operator:
 )
 ```
 
-![](fig/06_color_label_plot.png){alt='scatter plot of Hindfoot length vs weight (g) with colors coordinating to specfic species, showing abundance in the mid to lower left side of the plot'}
+![](fig/06_color_label_plot.png){alt='scatter plot of Hindfoot length vs weight (g) with colors coordinating to specific species, showing abundance in the mid to lower left side of the plot'}
 
 - Defining scale for colors, axes,... For example, a log-version of the x-axis
   could support the interpretation of the lower numbers:
@@ -387,7 +387,7 @@ mapping of a variable, `plotnine` will handle the values as category values.
 
 ## Plotting time series data
 
-Let's calculate number of counts per year for each species. To do that we need
+Let's calculate the number of counts per year for each species. To do that we need
 to group data first and count the species (`species_id`) within each group.
 
 ```python
@@ -567,7 +567,7 @@ following example of a bar plot with the counts per year.
 )
 ```
 
-![](fig/06_overlap_bars.png){alt='Bar graph of count per year showing ovelapping x-axis labels'}
+![](fig/06_overlap_bars.png){alt='Bar graph of count per year showing overlapping x-axis labels'}
 
 Notice that we use the `year` here as a categorical variable by using the
 `factor` functionality. However, by doing so, we have the individual year

md5sum.txt

@@ -9,9 +9,9 @@
 "episodes/02-starting-with-data.md" "bcd4e9564bd01585a52754fe4ad46f45" "site/built/02-starting-with-data.md" "2023-05-29"
 "episodes/03-index-slice-subset.md" "84263a14ba3f492bf6aa17435a78d905" "site/built/03-index-slice-subset.md" "2023-08-18"
 "episodes/04-data-types-and-format.md" "e57b9b771e5d2dcf4c9e2521822f8d5a" "site/built/04-data-types-and-format.md" "2023-06-05"
-"episodes/05-merging-data.md" "5e0cb1f86b8cb29a87d57b8eaee9acf5" "site/built/05-merging-data.md" "2024-02-05"
+"episodes/05-merging-data.md" "8491d51a41ad970f69acac6162e97432" "site/built/05-merging-data.md" "2024-02-21"
 "episodes/06-loops-and-functions.md" "d41f11e6c162c86393cd9bd4431c0687" "site/built/06-loops-and-functions.md" "2023-05-18"
-"episodes/07-visualization-ggplot-python.md" "814b6fc361595a0c9ea7db393b1424db" "site/built/07-visualization-ggplot-python.md" "2023-05-19"
+"episodes/07-visualization-ggplot-python.md" "90c47e103def226935f90723ae361b1f" "site/built/07-visualization-ggplot-python.md" "2024-02-21"
 "episodes/08-putting-it-all-together.md" "b279a4ab47789abda7f71609a78022ed" "site/built/08-putting-it-all-together.md" "2024-01-31"
 "episodes/09-working-with-sql.md" "e27af594f7ae68613dbaae8240493770" "site/built/09-working-with-sql.md" "2023-05-18"
 "instructors/CONTRIBUTORS.md" "71ca6d2e0d81004775e42ce90cd6a298" "site/built/CONTRIBUTORS.md" "2023-05-08"