Updated for df.append() deprecation.

Author: jtkiley

notebooks/1b_handling.ipynb

@@ -2120,15 +2120,27 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "results = pd.DataFrame()\n",
-    "for index, row in firmyear.loc[:, ['id_ticker', 'year']].iterrows():\n",
-    "    results = results.append(query_docs(msft_nyt, row['id_ticker'], row['year']))"
+    "result_list = []\n",
+    "for index, row in firmyear[['id_ticker', 'year']].iterrows():\n",
+    "    result_list.append(query_docs(msft_nyt, row['id_ticker'], row['year']))\n",
+    "results = pd.concat(result_list)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 33,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Here's the same operation condensed into a list comprehension.\n",
+    "# results = pd.concat([query_docs(msft_nyt, row['id_ticker'], row['year']) \n",
+    "#                      for i, row in firmyear[['id_ticker', 'year']].iterrows()])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -2214,7 +2226,7 @@
        "0      NaN     0.0      goog  2018"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 34,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2225,7 +2237,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
@@ -2347,7 +2359,7 @@
        "4      NaN     0.0  "
       ]
      },
-     "execution_count": 34,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2399,7 +2411,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2408,7 +2420,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2417,7 +2429,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2426,7 +2438,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2448,7 +2460,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
@@ -2570,7 +2582,7 @@
        "4      NaN     0.0  "
       ]
      },
-     "execution_count": 39,
+     "execution_count": 40,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2581,7 +2593,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [
     {
@@ -2640,7 +2652,7 @@
        "2  54.32  msft  2016"
       ]
      },
-     "execution_count": 40,
+     "execution_count": 41,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2651,7 +2663,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [
     {
@@ -2884,7 +2896,7 @@
        "[5 rows x 26 columns]"
       ]
      },
-     "execution_count": 41,
+     "execution_count": 42,
      "metadata": {},
      "output_type": "execute_result"
     }