Review tweaks

Author: craigsdennis

s2n4-combining-dataframes.ipynb

@@ -1,12 +1,5 @@
 {
  "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "[![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/treehouse-projects/python-introducing-pandas/master?filepath=s2n4-combining-dataframes.ipynb)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -39,7 +32,6 @@
     "from datetime import datetime\n",
     "import os\n",
     "\n",
-    "import numpy as np\n",
     "import pandas as pd\n",
     "\n",
     "from utils import render\n",
@@ -194,7 +186,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Ideally, I'd like to see all the requests that have a matching transaction based on the users and the amount involved.\n",
+    "I'd like to see all the requests that have a matching transaction based on the users and the amount involved.\n",
     "\n",
     "In order to do this we will merge both of our datasets together.  \n",
     "\n",
@@ -338,7 +330,7 @@
    "source": [
     "## Gather Insights\n",
     "\n",
-    "So looking at this data merged together, I'd like to see the difference between when the request was made, and when the money was actually received.\n",
+    "So looking at this data merged together, I'd like to see the time difference between when the request was made, and when the money was actually received.\n",
     "\n",
     "Good news for us, pandas has very powerful date/time functionality, but in order to get there we're going to need to convert our columns. As you can see, the CSV import did not recognize our date field.  **`sent_date`** and **`request_date`** are just plain old objects."
    ]
@@ -588,7 +580,7 @@
     "## Further research\n",
     "I saw something a little strange as I was looking through those **`successful_requests`**, it noticed a couple of what seemed like duplicated requests. I called my contact at CashBox and asked about possible duplicate requests.  Sure enough, the application allows you to send multiple requests for the same amount. \n",
     "\n",
-    "So this means there are probably duplicates in our **`successful_requests`** `DataFrame` because there are duplicates in the **`requests`**. There most like is only one transaction that fulfills the request, but there could be multiple requests that match. Our merge created duplication as well.\n",
+    "So this means there are probably duplicates in our **`successful_requests`** `DataFrame` because there are duplicates in the **`requests`**. There is most likely only one transaction that fulfills the request, but there could be multiple requests that match. Our merge brought that duplication across as well.\n",
     "\n",
     "Let's explore the possible duplicates in the **`requests`** `DataFrame`. There is a method [`DataFrame.duplicated`](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.duplicated.html) that will return a boolean `Series` which we can use as an index.  A `keep` parameter is available which is used to choose which of the duplicated rows to mark as a duplicate.  You can mark the first, last or all of them."
    ]