mergig

Merge branch 'master' of github.com:DS-100/textbook

content/_toc.yml

@@ -63,7 +63,6 @@ parts:
     - file: ch/07/sql_aggregating
     - file: ch/07/sql_joining
     - file: ch/07/sql_transforming
-    - file: ch/07/sql_other_reps
     - file: ch/07/sql_summary
 
 - caption: Understanding The Data

content/ch/07/sql_joining.ipynb

@@ -24,7 +24,7 @@
     "(sec:sql_joining)=\n",
     "# Joining\n",
     "\n",
-    "To connect records between two data tables, SQL relations can be joined together just like dataframes. In this section, we introduce SQL joins to replicate our analysis of the baby names data. Recall that {numref}`Chapter %s <ch:pandas>` mentions a New York Times article that talks about how certain name categories, like mythological and baby boomer names, have become more or less popular over time.\n",
+    "To connect records between two data tables, SQL relations can be joined together similar to dataframes. In this section, we introduce SQL joins to replicate our analysis of the baby names data. Recall that {numref}`Chapter %s <ch:pandas>` mentions a New York Times article that talks about how certain name categories, like mythological and baby boomer names, have become more or less popular over time.\n",
     "\n",
     "We've taken the names and categories in the NYT article and put them in a small relation named `nyt`:"
    ]
@@ -866,7 +866,7 @@
    "source": [
     ":::{note}\n",
     "\n",
-    "Notice that in the SQL code above, the numbers appear out of order---`[3]`, `[1]`, then `[2]`. We often think of the `SELECT` statement as the *last* piece of the query to execute although it appears first.\n",
+    "Notice that in the SQL code above, the numbers appear out of order---`[3]`, `[1]`, then `[2]`. As a rule of thumb for first-time SQL learners, we can often think of the `SELECT` statement as the *last* piece of the query to execute although it appears first.\n",
     "\n",
     ":::"
    ]

content/ch/07/sql_summary.ipynb

@@ -31,10 +31,7 @@
    "source": [
     "In this chapter, we explain what relations are, why they're useful, and\n",
     "how to work with them using SQL code.\n",
-    "Subsetting, aggregating, joining, and transforming are\n",
-    "useful in nearly every data analysis.\n",
-    "We'll rely on these operations often in the rest of the book, especially in\n",
-    "the {ref}`ch:files`, {ref}`ch:wrangling`, and {ref}`ch:eda` chapters."
+    "SQL databases are useful for many real-world settings. For example, SQL databases typically have robust data recovery mechanisms---if the computer crashes while in the middle of a SQL operation, the database system can recover as much data as possible without corruption. As mentioned earlier, SQL databases can also handle larger scale; organizations use SQL databases to store and query databases that are far too large to analyze in-memory using `pandas` code. These are just a few reasons why SQL is an important part of the data science toolbox, and we expect that many readers will soon encounter SQL code as part of their work."
    ]
   }
  ],