diff --git a/CSV_experiment.ipynb b/CSV_experiment.ipynb
index 8a4cf453ab41a03d5366e448c89e4085083ff53e..1e13a4c5b47eb26c88ecdcf9243c1cd0eed259fb 100644
--- a/CSV_experiment.ipynb
+++ b/CSV_experiment.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 89,
+   "execution_count": 105,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -13,6 +13,7 @@
     "import matplotlib as mpl\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
+    "plt.style.use('ggplot')\n",
     "plt.rcParams['text.usetex'] = True\n",
     "plt.rcParams['figure.dpi'] = 150\n",
     "plt.rcParams['savefig.dpi'] = 150\n",
@@ -20,8 +21,7 @@
     "#set_matplotlib_formats('svg')\n",
     "#plt.rcParams['figure.format'] = 'svg'\n",
     "pd.set_option('display.max_columns',85)\n",
-    "pd.set_option('display.max_rows',85)\n",
-    "plt.style.use('ggplot')"
+    "pd.set_option('display.max_rows',85)\n"
    ]
   },
   {
@@ -82,7 +82,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 90,
+   "execution_count": 106,
    "metadata": {},
    "outputs": [
     {
@@ -108,7 +108,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 107,
    "metadata": {},
    "outputs": [
     {
@@ -1031,7 +1031,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 101,
+   "execution_count": 102,
    "metadata": {},
    "outputs": [
     {
@@ -1262,7 +1262,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 88,
+   "execution_count": 103,
    "metadata": {},
    "outputs": [
     {
@@ -1293,7 +1293,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 86,
+   "execution_count": 104,
    "metadata": {},
    "outputs": [
     {
@@ -1330,7 +1330,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 300x300 with 1 Axes>"
       ]