Solange garrais

.ipynb_checkpoints/Untitled1-checkpoint.ipynb

@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

DataFrame_Groupby.py

@@ -1,5 +1,11 @@
-# -*- coding: utf-8 -*-
-__author__ = 'Who ?'
+"* -*- coding: utf-8 -*-"
+
+<<<<<<< HEAD
+"__message to author__ = 'solvethisconflict!'"
+=======
+__author__ = 'Antoine'
+#Stop messing with my name
+>>>>>>> origin
 
 import pandas as pd
 import numpy as np
@@ -24,7 +30,7 @@
 
 
 def cloneDF(df):
-    return pd.DataFrame(df.values.copy(), df.index.copy(), df.columns.copy()).convert_objects(convert_numeric=True)
+    return pd.DataFrame(df.values.copy(), df.index.copy(), df.columns.copy()).apply(pd.to_numeric, errors='coerce')
 
 
 # Show Films with more votes. (groupby + sorted)

DataFrame_pivot_table.py

@@ -1,5 +1,5 @@
 # -*- coding: utf-8 -*-
-__author__ = 'Who ?'
+__author__ = 'KwangilChi'
 
 import pandas as pd
 import numpy as np

Example_MovieLens.py

@@ -1,6 +1,8 @@
 # -*- coding: utf-8 -*-
 __author__ = 'Who ?'
 
+author == Solange
+
 import pandas as pd
 
 # Load users info

Series_vs_DataFrame.py

@@ -1,5 +1,6 @@
+
 # -*- coding: utf-8 -*-
-__author__ = 'Who ?'
+__author__ = 'Eugénie'
 
 import pandas as pd
 

Untitled.ipynb

@@ -0,0 +1,89 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'DataFrame_Groupby'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-5-78b7ea5b4db3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mDataFrame_Groupby\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'DataFrame_Groupby'"
+     ]
+    }
+   ],
+   "source": [
+    "import DataFrame_Groupby \n",
+    "\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
+  },
+  "varInspector": {
+   "cols": {
+    "lenName": 16,
+    "lenType": 16,
+    "lenVar": 40
+   },
+   "kernels_config": {
+    "python": {
+     "delete_cmd_postfix": "",
+     "delete_cmd_prefix": "del ",
+     "library": "var_list.py",
+     "varRefreshCmd": "print(var_dic_list())"
+    },
+    "r": {
+     "delete_cmd_postfix": ") ",
+     "delete_cmd_prefix": "rm(",
+     "library": "var_list.r",
+     "varRefreshCmd": "cat(var_dic_list()) "
+    }
+   },
+   "types_to_exclude": [
+    "module",
+    "function",
+    "builtin_function_or_method",
+    "instance",
+    "_Feature"
+   ],
+   "window_display": false
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

Untitled1.ipynb

@@ -0,0 +1,150 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Films with more votes: \n",
+      "Series([], dtype: int64)\n",
+      "\n",
+      "==================================================================\n",
+      "\n",
+      "Avg ratings: \n",
+      "Series([], Name: rating, dtype: int64)\n",
+      "\n",
+      "==================================================================\n",
+      "\n",
+      "Films ratings info: \n",
+      "Empty DataFrame\n",
+      "Columns: [mean, sum, count, std]\n",
+      "Index: []\n",
+      "\n",
+      "==================================================================\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/campus14/Documents/Git/4_collaborer/Example_Pandas/DataFrame_Groupby.py:57: FutureWarning: using a dict on a Series for aggregation\n",
+      "is deprecated and will be removed in a future version. Use                 named aggregation instead.\n",
+      "\n",
+      "    >>> grouper.agg(name_1=func_1, name_2=func_2)\n",
+      "\n",
+      "  {'SUM': np.sum, 'COUNT': np.size, 'AVG': np.mean, 'myAVG': lambda x: x.sum() / float(x.count())})\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "My info ratings: \n",
+      "Empty DataFrame\n",
+      "Columns: [SUM, COUNT, AVG, myAVG]\n",
+      "Index: []\n",
+      "\n",
+      "==================================================================\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/campus14/Documents/Git/4_collaborer/Example_Pandas/DataFrame_Groupby.py:65: FutureWarning: using a dict on a Series for aggregation\n",
+      "is deprecated and will be removed in a future version. Use                 named aggregation instead.\n",
+      "\n",
+      "    >>> grouper.agg(name_1=func_1, name_2=func_2)\n",
+      "\n",
+      "  {'COUNT': np.size, 'myAVG': lambda x: x.sum() / float(x.count())}).sort_values('COUNT', ascending=False)\n"
+     ]
+    },
+    {
+     "ename": "AttributeError",
+     "evalue": "'DataFrame' object has no attribute 'sort'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-4-9c185be770fb>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mDataFrame_Groupby\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;32m~/Documents/Git/4_collaborer/Example_Pandas/DataFrame_Groupby.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     63\u001b[0m \u001b[0msortRatingsField\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcloneDF\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmergeRatings\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     64\u001b[0m sortRatingsField = sortRatingsField.groupby(['movie_id', 'title'])['rating'].agg(\n\u001b[0;32m---> 65\u001b[0;31m     {'COUNT': np.size, 'myAVG': lambda x: x.sum() / float(x.count())}).sort('COUNT', ascending=False)\n\u001b[0m\u001b[1;32m     66\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'My info sorted: \\n%s'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0msortRatingsField\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m15\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m~/anaconda3/lib/python3.7/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m   5177\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_info_axis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_can_hold_identifiers_and_holds_name\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5178\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5179\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattribute__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   5180\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5181\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mAttributeError\u001b[0m: 'DataFrame' object has no attribute 'sort'"
+     ]
+    }
+   ],
+   "source": [
+    "from DataFrame_Groupby import *"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.4"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
+  },
+  "varInspector": {
+   "cols": {
+    "lenName": 16,
+    "lenType": 16,
+    "lenVar": 40
+   },
+   "kernels_config": {
+    "python": {
+     "delete_cmd_postfix": "",
+     "delete_cmd_prefix": "del ",
+     "library": "var_list.py",
+     "varRefreshCmd": "print(var_dic_list())"
+    },
+    "r": {
+     "delete_cmd_postfix": ") ",
+     "delete_cmd_prefix": "rm(",
+     "library": "var_list.r",
+     "varRefreshCmd": "cat(var_dic_list()) "
+    }
+   },
+   "types_to_exclude": [
+    "module",
+    "function",
+    "builtin_function_or_method",
+    "instance",
+    "_Feature"
+   ],
+   "window_display": false
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

delete_me.txt

@@ -0,0 +1 @@
+Delete this file when you find it

fruit.txt

@@ -0,0 +1,3 @@
+Name a red fruit then come up with a question:
+
+

tree_branch.txt

@@ -0,0 +1 @@
+