cleaned notebooks

data/big-random.csv

@@ -72,7 +72,8 @@ pedagogizzavano,12,vibratrice,92,striglio,58
 epigrammino,56,compravenduti,84,arzigogolava,55
 inibitoria,26,aerolinee,54,varero,88
 squarcerai,45,quiescenze,12,scuoieremo,70
-fantasmagorici,28,immischiavate,44,schiavizzammo,97,sfilzarono,49
+fantasmagorici,28,immischiavate,44
+schiavizzammo,97,sfilzarono,49
 interagiste,50,repentagli,72,attendato,95
 crossiste,17,maiolicheranno,24,espugniamo,64
 ribattezzava,36,contestataria,98,appezzino,60
@@ -710,7 +711,8 @@ barcheggiasti,36,subaccolleranno,44,libanizzavo,41
 salesiane,42,tutelai,40,sublimare,56
 intridevi,75,mazzuolavo,36,polemizzino,72
 resettando,58,strisciato,46,insaldai,62
-aspirasse,15,imbozzimatrici,70,incanalante,93,succhieremo,41
+aspirasse,15,imbozzimatrici,70
+incanalante,93,succhieremo,41
 saccarometriche,18,stremaste,12,hindi,19
 immergano,99,estolta,99,resistenti,68
 schiavo,13,carrellavamo,50,scimmiotti,23
@@ -8094,7 +8096,8 @@ querelavate,97,carella,49,artocebo,74
 intercludeva,37,brezzoline,87,viceprovincia,16
 sviarono,49,disalveante,37,raschierete,12
 squincio,16,biascicona,93,solisti,70
-rinegoziante,50,circoncidiamo,83,stringavate,79,stipularono,34
+rinegoziante,50,circoncidiamo,83
+stringavate,79,stipularono,34
 disaeriamo,94,sfiorisce,37,mesterebbe,46
 inosservanti,45,esporrei,98,angustiosi,21
 spalmeresti,18,interromperai,20,notifichiate,54
@@ -12292,7 +12295,8 @@ smozzante,98,scalfendo,29,indirizzavo,23
 sprovvedevi,90,nepentacee,13,raffinasti,69
 raddobbassi,10,tortoreggiate,24,telecomandavamo,27
 stremeranno,89,trastullassi,79,rinsavireste,20
-palettizzassimo,50,colliquerei,26,scarseggiata,93,schioppetteria,63
+palettizzassimo,50,colliquerei,26
+scarseggiata,93,schioppetteria,63
 imperammo,47,baluginano,61,premoriranno,59
 rivisita,12,agguanteresti,47,isotropo,87
 polifonie,10,attufferai,17,legiferavo,36

notebooks/01_introduction.ipynb

@@ -10,16 +10,6 @@
     "\n",
     "Eva Zangerle\n",
     "\n",
-    "## Overview of Notebooks\n",
-    "* Datasets: [3_datasets.ipynb](3_datasets.ipynb)\n",
-    "* Data Preparation and Quality: [4_data_preparation_quality.ipynb](4_data_preparation_quality.ipynb)\n",
-    "* Feature Engineering: [5_feature_engineering.ipynb](5_feature_engineering.ipynb)\n",
-    "* Dataset Analyses: [6_dataset_analyses.ipynb](6_dataset_analyses.ipynb)\n",
-    "* Hypotheses and Evaluation: [7_hypotheses_evaluation.ipynb](7_hypotheses_evaluation.ipynb)\n",
-    "* Modeling and Prediction: [8_modeling_prediction.ipynb](8_modeling_prediction.ipynb)\n",
-    "* Reproducible Research: [9_reproducible_research.ipynb](9_reproducible_research.ipynb)\n",
-    "\n",
-    "\n",
     "## General Notes\n",
     "* Code is partly taken from further sources, such as books.\n",
     "* Sources are annotated (and acknowledged!) as follows:\n",
@@ -43,19 +33,11 @@
     "## Useful python stuff\n",
     "* Startup files: https://ipython.readthedocs.io/en/stable/interactive/tutorial.html#startup-files\n",
     "* tqdm progress bars (also for Jupyter): https://github.com/tqdm/tqdm\n",
+    "* nbval for validating Jupyter notebooks: https://github.com/computationalmodelling/nbval\n",
+    "* nbqa for quality assurance for Jupyter notebooks: https://github.com/nbQA-dev/nbQA\n",
     "\n",
     "## Further tools\n",
-    "* jq command linen json processor: https://stedolan.github.io/jq/\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "f6860d72-11e4-4574-b20b-7884a6653abc",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    " "
+    "* jq command line json processor: https://stedolan.github.io/jq/"
    ]
   }
  ],
@@ -75,7 +57,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.9.7"
   }
  },
  "nbformat": 4,

notebooks/07_feature_engineering.ipynb

@@ -19,10 +19,11 @@
    "source": [
     "# import required packages\n",
     "from pprint import pprint\n",
-    "from scipy.stats import gmean, hmean\n",
-    "from sklearn.datasets import load_digits\n",
+    "\n",
     "from matplotlib import cm\n",
-    "from matplotlib.colors import ListedColormap"
+    "from matplotlib.colors import ListedColormap\n",
+    "from scipy.stats import gmean, hmean\n",
+    "from sklearn.datasets import load_digits"
    ]
   },
   {