Merge pull request #32 from datapartnership/update_notebook_info

update notebooks
datapartnership · Jun 4, 2024 · b3d4635 · b3d4635
2 parents e32f335 + db61f65
commit b3d4635
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diff --git a/notebooks/mobility/activity.ipynb b/notebooks/mobility/activity.ipynb
@@ -2000,6 +2000,14 @@
     "### By Special Economic Zones"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "1880cae1-fabc-4633-8574-7211650b54fd",
+   "metadata": {},
+   "source": [
+    "#### Percentage Change"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 24,
@@ -2046,6 +2054,14 @@
     "plt.savefig(\"percentage_change.png\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "9587f296-6638-40f5-bf4b-8e4c7593b6f5",
+   "metadata": {},
+   "source": [
+    "#### Z-Score"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 26,
@@ -2120,6 +2136,14 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "78a9325d-2a4c-4a77-bda5-9edd8b624a5f",
+   "metadata": {},
+   "source": [
+    "#### Percentage Change"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 28,
@@ -2170,6 +2194,14 @@
     "plt.savefig(\"percentage_change_admin1.png\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "9b773bf9-fa68-497f-b603-44e242077502",
+   "metadata": {},
+   "source": [
+    "#### Z-Score"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 29,
@@ -2219,6 +2251,14 @@
     "plt.savefig(\"z_score_admin1.png\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "5e144119-e8ed-4227-bb22-b5af91d6ab2d",
+   "metadata": {},
+   "source": [
+    "### By Region"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 30,
@@ -2256,6 +2296,14 @@
     "ACTIVITY[\"region\"] = ACTIVITY[\"admin1\"].apply(lambda x: region_dict[x])"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "1b364faf-806a-400a-bbe6-94c30bff5cb5",
+   "metadata": {},
+   "source": [
+    "#### Percentage Change"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 38,
@@ -2306,6 +2354,14 @@
     "plt.savefig(\"percentage_change_region.png\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "8eed30b3-3c6c-49ab-818a-7e004921b7f4",
+   "metadata": {},
+   "source": [
+    "#### Z-Score"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 37,
@@ -3019,7 +3075,7 @@
   ],
   "instance_type": "ml.m5.16xlarge",
   "kernelspec": {
-   "display_name": "data-goods",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -3033,7 +3089,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

diff --git a/notebooks/mobility/mobility.ipynb b/notebooks/mobility/mobility.ipynb
@@ -253,62 +253,6 @@
     "plt.xticks(rotation=90);"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "37a8b4e1-8816-4988-9a24-ad714f269b4e",
-   "metadata": {
-    "tags": [
-     "remove-input"
-    ]
-   },
-   "source": [
-    "### ID type"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "abfe4f36-a7d0-4033-bfa3-7f7b0b9908ef",
-   "metadata": {
-    "tags": [
-     "remove-input"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "path = \"./data/data*.parquet\"\n",
-    "columns = [\"uid\", \"datetime\", \"id_type\"]\n",
-    "ddf = dd.read_parquet(path, columns=columns)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "fac8ead5-a8c1-4de5-b518-ae2f476e282d",
-   "metadata": {
-    "tags": [
-     "remove-input"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "# ddf.groupby(['uid', 'id_type']).size().head()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b6d90836-1f89-412b-a2fd-e89ce8455509",
-   "metadata": {
-    "tags": [
-     "remove-input"
-    ]
-   },
-   "outputs": [],
-   "source": [
-    "agg_by_id_type"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "8ce0dc2a-9628-4806-981f-adb0e618ed0a",
@@ -508,7 +452,7 @@
    "metadata": {},
    "source": [
     "### Users suitable for a longitudinal analysis\n",
-    "In order to perform a longitudinal analysis, we are filtering the data to keep only useres that had at least 30 pings in a month, which are around 2,500,000. \n",
+    "In order to perform a longitudinal analysis, we are filtering the data to keep only useres that had at least 30 pings in a month, which are around 1,300,000. \n",
     "Then, we check for how many months these users keep these level of connection intensity. We observe that 75% of the users were able to keep the 30 pings per month for less than 2 months of the total 51 months. None of the users were able to keep the 30 pings per month across the 4 years.  \n"
    ]
   },