diff --git a/lab_1/lab1.ipynb b/lab_1/lab1.ipynb index 155007f..93e6167 100644 --- a/lab_1/lab1.ipynb +++ b/lab_1/lab1.ipynb @@ -11,7 +11,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -27,6 +27,8 @@ ], "source": [ "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.dates as md\n", "\n", "df = pd.read_csv(\"..//..//static//csv//StudentsPerformance.csv\")\n", "print (df.columns)" @@ -34,53 +36,49 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 10, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "RangeIndex: 1000 entries, 0 to 999\n", - "Data columns (total 8 columns):\n", - " # Column Non-Null Count Dtype \n", - "--- ------ -------------- ----- \n", - " 0 gender 1000 non-null object\n", - " 1 race/ethnicity 1000 non-null object\n", - " 2 parental level of education 1000 non-null object\n", - " 3 lunch 1000 non-null object\n", - " 4 test preparation course 1000 non-null object\n", - " 5 math score 1000 non-null int64 \n", - " 6 reading score 1000 non-null int64 \n", - " 7 writing score 1000 non-null int64 \n", - "dtypes: int64(3), object(5)\n", - "memory usage: 62.6+ KB\n" + "ename": "TypeError", + "evalue": "'RangeIndex' object is not callable", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[10], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mdf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mindex\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m)\u001b[49m\n", + "\u001b[1;31mTypeError\u001b[0m: 'RangeIndex' object is not callable" ] } ], "source": [ - "df.info()" + "df.index(2)" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 3, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - " count mean std min 25% 50% 75% max\n", - "math score 1000.0 66.089 15.163080 0.0 57.00 66.0 77.0 100.0\n", - "reading score 1000.0 69.169 14.600192 17.0 59.00 70.0 79.0 100.0\n", - "writing score 1000.0 68.054 15.195657 10.0 57.75 69.0 79.0 100.0\n" + "ename": "ImportError", + "evalue": "matplotlib is required for plotting when the default backend \"matplotlib\" is selected.", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mImportError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[3], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mdf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mplot\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhist\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcolumn\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmath score\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbins\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m80\u001b[39;49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32mc:\\Users\\Наталья\\Desktop\\5semestr\\AIM\\aimenv\\Lib\\site-packages\\pandas\\plotting\\_core.py:1409\u001b[0m, in \u001b[0;36mPlotAccessor.hist\u001b[1;34m(self, by, bins, **kwargs)\u001b[0m\n\u001b[0;32m 1349\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mhist\u001b[39m(\n\u001b[0;32m 1350\u001b[0m \u001b[38;5;28mself\u001b[39m, by: IndexLabel \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m, bins: \u001b[38;5;28mint\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m10\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs\n\u001b[0;32m 1351\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m PlotAccessor:\n\u001b[0;32m 1352\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m 1353\u001b[0m \u001b[38;5;124;03m Draw one histogram of the DataFrame's columns.\u001b[39;00m\n\u001b[0;32m 1354\u001b[0m \n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 1407\u001b[0m \u001b[38;5;124;03m >>> ax = df.plot.hist(column=[\"age\"], by=\"gender\", figsize=(10, 8))\u001b[39;00m\n\u001b[0;32m 1408\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m-> 1409\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mkind\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mhist\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mby\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mby\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbins\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbins\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32mc:\\Users\\Наталья\\Desktop\\5semestr\\AIM\\aimenv\\Lib\\site-packages\\pandas\\plotting\\_core.py:947\u001b[0m, in \u001b[0;36mPlotAccessor.__call__\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m 946\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__call__\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m--> 947\u001b[0m plot_backend \u001b[38;5;241m=\u001b[39m \u001b[43m_get_plot_backend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpop\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mbackend\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 949\u001b[0m x, y, kind, kwargs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_call_args(\n\u001b[0;32m 950\u001b[0m plot_backend\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_parent, args, kwargs\n\u001b[0;32m 951\u001b[0m )\n\u001b[0;32m 953\u001b[0m kind \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_kind_aliases\u001b[38;5;241m.\u001b[39mget(kind, kind)\n", + "File \u001b[1;32mc:\\Users\\Наталья\\Desktop\\5semestr\\AIM\\aimenv\\Lib\\site-packages\\pandas\\plotting\\_core.py:1944\u001b[0m, in \u001b[0;36m_get_plot_backend\u001b[1;34m(backend)\u001b[0m\n\u001b[0;32m 1941\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m backend_str \u001b[38;5;129;01min\u001b[39;00m _backends:\n\u001b[0;32m 1942\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _backends[backend_str]\n\u001b[1;32m-> 1944\u001b[0m module \u001b[38;5;241m=\u001b[39m \u001b[43m_load_backend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbackend_str\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1945\u001b[0m _backends[backend_str] \u001b[38;5;241m=\u001b[39m module\n\u001b[0;32m 1946\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m module\n", + "File \u001b[1;32mc:\\Users\\Наталья\\Desktop\\5semestr\\AIM\\aimenv\\Lib\\site-packages\\pandas\\plotting\\_core.py:1874\u001b[0m, in \u001b[0;36m_load_backend\u001b[1;34m(backend)\u001b[0m\n\u001b[0;32m 1872\u001b[0m module \u001b[38;5;241m=\u001b[39m importlib\u001b[38;5;241m.\u001b[39mimport_module(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpandas.plotting._matplotlib\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 1873\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m:\n\u001b[1;32m-> 1874\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m(\n\u001b[0;32m 1875\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmatplotlib is required for plotting when the \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 1876\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdefault backend \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmatplotlib\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m is selected.\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m 1877\u001b[0m ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m 1878\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m module\n\u001b[0;32m 1880\u001b[0m found_backend \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n", + "\u001b[1;31mImportError\u001b[0m: matplotlib is required for plotting when the default backend \"matplotlib\" is selected." ] } ], "source": [ - "print(df.describe().transpose())" + "\n", + "df.plot.hist(column=[\"math score\"], bins=80)" ] } ],