@@ -278,7 +278,7 @@ surveys_df[0:3]
278278>
279279> _Remember: R begins indexing lists at 1._
280280>
281- > > ## Solution
281+ <!-- > > ## Solution
282282> >
283283> > With the same list:
284284> > `['A','B','C','D','E','F','G','H','I','J']`,
@@ -315,7 +315,7 @@ surveys_df[0:3]
315315> > This is ignored when you use the syntax
316316> > `x[0:5]`, and the elements in `1` through
317317> > `5` are printed.
318- > {: .solution}
318+ > {: .solution} -->
319319{: .challenge}
320320
321321
@@ -325,7 +325,7 @@ surveys_df[0:3]
325325> Combine selecting a subset with column headings and slice syntax for rows. Get
326326> every 5th row for rows 20-60, from the columns `plot_id`, `species_id`, and `sex`.
327327>
328- > > ## Solution
328+ <!-- > > ## Solution
329329> >
330330> > ~~~
331331> > surveys_df[['plot_id', 'species_id','sex']][20:61:5]
@@ -345,7 +345,7 @@ surveys_df[0:3]
345345> > 60 23 DM M
346346> > ~~~
347347> > {: .output}
348- > {: .solution}
348+ > {: .solution} -->
349349{: .challenge}
350350
351351## Changing Values in a DataFrame
@@ -610,7 +610,7 @@ surveys_df.loc[1:4, ['record_id','month']]
610610>
611611> 2. Use `.iloc[]` to view the same thing.
612612>
613- > > ## Solution
613+ <!-- > > ## Solution
614614> >
615615> > ~~~
616616> > # 1
@@ -620,7 +620,7 @@ surveys_df.loc[1:4, ['record_id','month']]
620620> > surveys_df.iloc[1:6:2, [5,6]]
621621> > ~~~
622622> > {: .python}
623- > {: .solution}
623+ > {: .solution} -->
624624{: .challenge}
625625
626626
@@ -674,7 +674,7 @@ surveys_df[(surveys_df.sex == 'M') & (surveys_df.year <= 1985)]
674674> the year 1999 and that contain weight values less than or equal to 8. How
675675> many rows did you end up with?
676676>
677- > > ## Solution
677+ <!-- > > ## Solution
678678> >
679679> > ~~~
680680> > surveys_df[(surveys_df.weight <= 8.0) & (surveys_df.year == 1999)]
@@ -696,7 +696,7 @@ surveys_df[(surveys_df.sex == 'M') & (surveys_df.year <= 1985)]
696696> > 29905 4.0
697697> > ~~~
698698> > {: .output}
699- > {: .solution}
699+ > {: .solution} -->
700700{: .challenge}
701701
702702## Iterating Over a DataFrame
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