The goal of this assignment is to practice working with CSV files and using NumPy functions. Please follow the following steps using the Jupyter Notebook Please count the number of characters in your...

{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Mohamed Aljahani "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Assignment 01 - Cu
ent Date: 2020-10-10"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Sex Weight_Sep Weight_Apr BMI_Sep BMI_Apr\n",
"0 M 72 59 22.02 18.14\n",
"1 M 97 86 19.70 17.44\n",
"2 M 74 69 24.09 22.43\n",
"3 M 93 88 26.97 25.57\n",
"4 F 68 64 21.51 20.10\n",
"5 M 59 55 18.69 17.40\n",
"6 F 64 60 24.24 22.88\n",
"7 F 56 53 21.23 20.23\n",
"8 F 70 68 30.26 29.24\n",
"9 F 58 56 21.88 21.02\n",
"10 F 50 47 17.63 16.89\n",
"11 M 71 69 24.57 23.85\n",
"12 M 67 66 20.68 20.15\n",
"13 F 56 55 20.97 20.36\n",
"14 F 70 68 27.30 26.73\n",
"15 F 61 60 23.30 22.88\n",
"16 F 53 52 19.48 19.24\n",
"17 M 92 92 24.74 24.69\n",
"18 F 57 58 20.69 20.79\n",
"19 M 67 67 20.49 20.60\n",
"20 F 58 58 21.09 21.24\n",
"21 F 49 50 18.37 18.53\n",
"22 M 68 68 22.40 22.61\n",
"23 F 69 69 28.17 28.43\n",
"24 M 87 88 23.60 23.81\n",
"25 M 81 82 26.52 26.78\n",
"26 M 60 61 18.89 19.27\n",
"27 F 52 53 19.31 19.75\n",
"28 M 70 71 20.96 21.32\n",
"29 F 63 64 21.78 22.22\n",
".. .. ... ... ... ...\n",
"37 F 63 65 23.87 24.67\n",
"38 F 54 56 18.61 19.34\n",
"39 F 56 58 21.73 22.58\n",
"40 M 54 56 18.93 19.72\n",
"41 M 73 75 25.88 26.72\n",
"42 M 77 79 28.59 29.53\n",
"43 F 63 66 21.89 22.79\n",
"44 F 51 54 18.31 19.28\n",
"45 F 59 62 19.64 20.63\n",
"46 F 65 68 23.02 24.10\n",
"47 F 53 56 20.63 21.91\n",
"48 F 62 65 22.61 23.81\n",
"49 F 55 58 22.03 23.42\n",
"50 M 74 77 20.31 21.34\n",
"51 M 74 78 20.31 21.36\n",
"52 M 64 68 19.59 20.77\n",
"53 M 64 68 21.05 22.31\n",
"54 F 57 61 23.47 25.11\n",
"55 F 64 68 22.84 24.29\n",
"56 F 60 64 19.50 20.90\n",
"57 M 64 68 18.51 19.83\n",
"58 M 66 71 21.40 22.97\n",
"59 F 52 57 17.72 19.42\n",
"60 M 71 77 22.26 23.87\n",
"61 F 55 60 21.64 23.81\n",
"62 M 65 71 22.51 24.45\n",
"63 M 75 82 23.69 25.80\n",
"64 F 42 49 15.08 17.74\n",
"65 M 74 82 22.64 25.33\n",
"66 M 94 105 36.57 40.86\n",
"\n",
"[67 rows x 5 columns]\n"
]
}
],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"#Function defined for reading the data from a csv file.\n",
"def readFile():\n",
" df=pd.read_csv(r'Give path to the csv file in your computer\\freshman_kgs.csv')\n",
" df=pd.DataFrame(df)\n",
" return(df)\n",
"ds=readFile();\n",
"print(ds);"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 72\n",
"1 97\n",
"2 74\n",
"3 93\n",
"4 68\n",
"5 59\n",
"6 64\n",
"7 56\n",
"8 70\n",
"9 58\n",
"10 50\n",
"11 71\n",
"12 67\n",
"13 56\n",
"14 70\n",
"15 61\n",
"16 53\n",
"17 92\n",
"18 57\n",
"19 67\n",
"20 58\n",
"21 49\n",
"22 68\n",
"23 69\n",
"24 87\n",
"25 81\n",
"26 60\n",
"27 52\n",
"28 70\n",
"29 63\n",
" ..\n",
"37 63\n",
"38 54\n",
"39 56\n",
"40 54\n",
"41 73\n",
"42 77\n",
"43 63\n",
"44 51\n",
"45 59\n",
"46 65\n",
"47 53\n",
"48 62\n",
"49 55\n",
"50 74\n",
"51 74\n",
"52 64\n",
"53 64\n",
"54 57\n",
"55 64\n",
"56 60\n",
"57 64\n",
"58 66\n",
"59 52\n",
"60 71\n",
"61 55\n",
"62 65\n",
"63 75\n",
"64 42\n",
"65 74\n",
...