ok

ads_query.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -16,7 +16,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -25,7 +25,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -41,7 +41,9 @@
     "# format the response in a nicely readable format\n",
     "results_first = response_first.json()\n",
     "\n",
-    "\n",
+    "# save it\n",
+    "with open('data/ads_data_first.json', 'w') as f:\n",
+    "    json.dump(results_first, f, indent=4)\n",
     "\n",
     "# all papers\n",
     "encoded_query_all = urlencode({\"q\": \"author:peca, alessandro\",\n",
@@ -56,13 +58,13 @@
     "results_all = response_all.json()\n",
     "\n",
     "# save it\n",
-    "with open('data/ads_data.json', 'w') as f:\n",
-    "    json.dump(results_first, f, indent=4)\n"
+    "with open('data/ads_data_all.json', 'w') as f:\n",
+    "    json.dump(results_all, f, indent=4)\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
@@ -80,10 +82,10 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x14077c150>"
+       "<matplotlib.legend.Legend at 0x14075b1d0>"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -159,7 +161,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
@@ -515,7 +517,7 @@
        "  'citation_count': 2}]"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }