feat: naming column in coverage df

Author: slebastard

notebooks/02-rapport_post_integration.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "relevant-fighter",
+   "id": "mental-deployment",
    "metadata": {},
    "source": [
     "# Automated Post-integration Report - Signaux Faibles\n",
@@ -12,7 +12,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "straight-detroit",
+   "id": "stock-shame",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -56,7 +56,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "turkish-newport",
+   "id": "adjustable-arkansas",
    "metadata": {},
    "source": [
     "## Fetch a random sample of the data"
@@ -65,7 +65,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "reported-peoples",
+   "id": "false-shield",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -76,7 +76,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "married-drinking",
+   "id": "formed-salvation",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -86,7 +86,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "authentic-rendering",
+   "id": "suspended-london",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -99,7 +99,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "presidential-acrobat",
+   "id": "pediatric-drama",
    "metadata": {},
    "source": [
     "## Temporal Coverage and NA values"
@@ -108,7 +108,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "monthly-secretary",
+   "id": "theoretical-density",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -118,7 +118,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "otherwise-culture",
+   "id": "promotional-heritage",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -129,16 +129,18 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "sexual-chester",
+   "id": "included-industry",
    "metadata": {},
    "outputs": [],
    "source": [
-    "(dataset.data.isna().sum() / len(dataset) * 100).sort_values(ascending = False).to_frame()"
+    "na_rates_df = (dataset.data.isna().sum() / len(dataset) * 100).sort_values(ascending = False).to_frame()\n",
+    "na_rates_df.columns = [\"NA rate\"]\n",
+    "na_rates_df"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "oriental-flush",
+   "id": "logical-bailey",
    "metadata": {},
    "source": [
     "## Coverage over time for selected variables"
@@ -147,7 +149,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "historical-brick",
+   "id": "fiscal-samoa",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -158,7 +160,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "awful-nurse",
+   "id": "handled-tuning",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -179,33 +181,33 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "lucky-clerk",
+   "id": "critical-category",
    "metadata": {},
    "outputs": [],
    "source": []
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "proud-volunteer",
+   "id": "super-arabic",
    "metadata": {},
    "outputs": [],
    "source": []
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "sensitive-pipeline",
+   "id": "desperate-button",
    "metadata": {},
    "outputs": [],
    "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "sf",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "sf"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {