[translations] Fixed format that affects translations on 7 file(s).

_episodes/01-run-quit.md

@@ -53,7 +53,6 @@ does not require an internet connection.
 > Experienced users of Jupyter notebooks interested in a more detailed discussion of the similarities and differences
 > between the JupyterLab and Jupyter notebook user interfaces can find more information in the 
 > [JupyterLab user interface documentation][jupyterlab-ui].
->
 {: .callout}
 
 ## Starting JupyterLab
@@ -202,7 +201,6 @@ more details, then see the [official notebook documentation][jupyterlab-notebook
 > > After creating the necessary tabs, you can drag one of the tabs to the center of a panel to 
 > > move the tab to the panel; next you can subdivide a tab panel by dragging a tab to the left, 
 > > right, top, or bottom of the panel.
-> >
 > {: .solution}
 {: .challenge}
 
@@ -254,7 +252,6 @@ more details, then see the [official notebook documentation][jupyterlab-notebook
 > > You need to be in Command mode (Press <kbd>Esc</kbd> if your cell is blue).  Type <kbd>b</kbd> or <kbd>a</kbd>.
 > > You need to be in Command mode (Press <kbd>Esc</kbd> if your cell is blue).  Type <kbd>x</kbd>.
 > > You need to be in Command mode (Press <kbd>Esc</kbd> if your cell is blue).  Type <kbd>z</kbd>.
-> >
 > {: .solution}
 {: .challenge}
 
@@ -512,7 +509,6 @@ $ jupyter lab
 > ## Closing JupyerLab
 >
 > Practice closing and restarting the JupyterLab server.
-> 
 {: .challenge}
 [anaconda]: https://docs.continuum.io/anaconda/install
 [jupyterlab-ui]: https://jupyterlab.readthedocs.io/en/stable/user/interface.html

_episodes/02-variables.md

@@ -349,6 +349,5 @@ print(ewr_422_yY, 'is', flabadab, 'years old')
 > > 4. `thing[:]` returns all of `thing`
 > > 5. `thing[number:some-negative-number]` returns a slice from `number` to `some-negative-number` values from the end of `thing`
 > > 6. If a part of the slice is out of range, the operation does not fail. `atom_name[0:15]` gives the same result as `atom_name[0:]`.
-> >
 > {: .solution}
 {: .challenge}

_episodes/03-types-conversion.md

@@ -269,7 +269,6 @@ first is 2 and second is 5
 > > 4. This will vary! How do you define a specimen's age? whole days since collection (integer)? date and time (string)?
 > > 5. Choose floating point to represent population as large aggregates (eg millions), or integer to represent population in units of individuals.
 > > 6. Floating point number, since an average is likely to have a fractional part.
-> >
 > > {: .output}
 > {: .solution}
 {: .challenge}

_episodes/06-libraries.md

@@ -146,7 +146,6 @@ cos(pi) is -1.0
 > >    Also, the design of Python's `math` library has its origin in the C standard,
 > >    which includes both `sqrt(x)` and `pow(x,y)`, so a little bit of the history
 > >    of programming is showing in Python's function names.
-> >
 > {: .solution}
 {: .challenge}
 
@@ -235,7 +234,6 @@ cos(pi) is -1.0
 > > print("random base", bases[idx], "base index", idx)
 > > ~~~
 > > {: .language-python}
-> >
 > {: .solution}
 {: .challenge}
 

_episodes/07-reading-tabular.md

@@ -384,6 +384,5 @@ max      23424.766830    26997.936570    30687.754730    34435.367440
 > >{: .language-python}
 > > Note that `help(to_csv)` throws an error! This is a subtlety and is due to the fact that `to_csv` is NOT a function in 
 > > and of itself and the actual call is `americas.to_csv`. 
-> > 
 > {: .solution}
 {: .challenge}

_episodes/08-data-frames.md

@@ -366,7 +366,6 @@ data.groupby(wealth_score).sum()
 > print(df.loc['Albania':'Belgium', 'gdpPercap_1952':'gdpPercap_1962'])
 > ~~~
 > {: .language-python}
-> 
 {: .challenge}
 > 
 > > ## Solution

_episodes/09-plotting.md

@@ -149,7 +149,6 @@ plt.ylabel('GDP per capita ($)')
 > By default matplotlib will attempt to place the legend in a suitable position. If you
 > would rather specify a position this can be done with the `loc=` argument, e.g to place
 > the legend in the upper left corner of the plot, specify `loc='upper left'`
->
 > {: .language-python}
 {: .callout}
 
@@ -219,7 +218,6 @@ data.T.plot.scatter(x = 'Australia', y = 'New Zealand')
 > >
 > > No particular correlations can be seen between the minimum and maximum gdp values
 > > year on year. It seems the fortunes of asian countries do not rise and fall together.
-> >
 > {: .solution}
 >
 > You might note that the variability in the maximum is much higher than
@@ -240,7 +238,6 @@ data.T.plot.scatter(x = 'Australia', y = 'New Zealand')
 > > maybe the Brent crude index would make an interesting comparison?
 > > Whilst Myanmar consistently has the lowest gdp, the highest gdb nation has varied
 > > more notably.
-> >
 > {: .solution}
 {: .challenge}
 
@@ -274,7 +271,6 @@ data.T.plot.scatter(x = 'Australia', y = 'New Zealand')
 > > s - Details for this can be found in the documentation of plt.scatter.
 > > A single number or one value for each data point. Determines the size
 > > of the plotted points.
-> >
 > {: .solution}
 {: .challenge}