{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Student Alcohol Consumption"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Introduction:\n",
"\n",
"This time you will download a dataset from the UCI.\n",
"\n",
"### Step 1. Import the necessary libraries"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import numpy"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Step 2. Import the dataset from this [address](https://github.com/guipsamora/pandas_exercises/blob/master/04_Apply/Students_Alcohol_Consumption/student-mat.csv)."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Step 3. Assign it to a variable called df."
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"
\n",
" \n",
" \n",
" | \n",
" school | \n",
" sex | \n",
" age | \n",
" address | \n",
" famsize | \n",
" Pstatus | \n",
" Medu | \n",
" Fedu | \n",
" Mjob | \n",
" Fjob | \n",
" ... | \n",
" famrel | \n",
" freetime | \n",
" goout | \n",
" Dalc | \n",
" Walc | \n",
" health | \n",
" absences | \n",
" G1 | \n",
" G2 | \n",
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" teacher | \n",
" ... | \n",
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" 1 | \n",
" 1 | \n",
" at_home | \n",
" other | \n",
" ... | \n",
" 5 | \n",
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" at_home | \n",
" other | \n",
" ... | \n",
" 4 | \n",
" 3 | \n",
" 2 | \n",
" 2 | \n",
" 3 | \n",
" 3 | \n",
" 10 | \n",
" 7 | \n",
" 8 | \n",
" 10 | \n",
"
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" \n",
" 3 | \n",
" GP | \n",
" F | \n",
" 15 | \n",
" U | \n",
" GT3 | \n",
" T | \n",
" 4 | \n",
" 2 | \n",
" health | \n",
" services | \n",
" ... | \n",
" 3 | \n",
" 2 | \n",
" 2 | \n",
" 1 | \n",
" 1 | \n",
" 5 | \n",
" 2 | \n",
" 15 | \n",
" 14 | \n",
" 15 | \n",
"
\n",
" \n",
" 4 | \n",
" GP | \n",
" F | \n",
" 16 | \n",
" U | \n",
" GT3 | \n",
" T | \n",
" 3 | \n",
" 3 | \n",
" other | \n",
" other | \n",
" ... | \n",
" 4 | \n",
" 3 | \n",
" 2 | \n",
" 1 | \n",
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" 5 | \n",
" 4 | \n",
" 6 | \n",
" 10 | \n",
" 10 | \n",
"
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" \n",
"
\n",
"
5 rows × 33 columns
\n",
"
"
],
"text/plain": [
" school sex age address famsize Pstatus Medu Fedu Mjob Fjob ... \\\n",
"0 GP F 18 U GT3 A 4 4 at_home teacher ... \n",
"1 GP F 17 U GT3 T 1 1 at_home other ... \n",
"2 GP F 15 U LE3 T 1 1 at_home other ... \n",
"3 GP F 15 U GT3 T 4 2 health services ... \n",
"4 GP F 16 U GT3 T 3 3 other other ... \n",
"\n",
" famrel freetime goout Dalc Walc health absences G1 G2 G3 \n",
"0 4 3 4 1 1 3 6 5 6 6 \n",
"1 5 3 3 1 1 3 4 5 5 6 \n",
"2 4 3 2 2 3 3 10 7 8 10 \n",
"3 3 2 2 1 1 5 2 15 14 15 \n",
"4 4 3 2 1 2 5 4 6 10 10 \n",
"\n",
"[5 rows x 33 columns]"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Step 4. For the purpose of this exercise slice the dataframe from 'school' until the 'guardian' column"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
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" \n",
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" | \n",
" school | \n",
" sex | \n",
" age | \n",
" address | \n",
" famsize | \n",
" Pstatus | \n",
" Medu | \n",
" Fedu | \n",
" Mjob | \n",
" Fjob | \n",
" reason | \n",
" guardian | \n",
"
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" 0 | \n",
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" F | \n",
" 18 | \n",
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" A | \n",
" 4 | \n",
" 4 | \n",
" at_home | \n",
" teacher | \n",
" course | \n",
" mother | \n",
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" U | \n",
" GT3 | \n",
" T | \n",
" 1 | \n",
" 1 | \n",
" at_home | \n",
" other | \n",
" course | \n",
" father | \n",
"
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" \n",
" 2 | \n",
" GP | \n",
" F | \n",
" 15 | \n",
" U | \n",
" LE3 | \n",
" T | \n",
" 1 | \n",
" 1 | \n",
" at_home | \n",
" other | \n",
" other | \n",
" mother | \n",
"
\n",
" \n",
" 3 | \n",
" GP | \n",
" F | \n",
" 15 | \n",
" U | \n",
" GT3 | \n",
" T | \n",
" 4 | \n",
" 2 | \n",
" health | \n",
" services | \n",
" home | \n",
" mother | \n",
"
\n",
" \n",
" 4 | \n",
" GP | \n",
" F | \n",
" 16 | \n",
" U | \n",
" GT3 | \n",
" T | \n",
" 3 | \n",
" 3 | \n",
" other | \n",
" other | \n",
" home | \n",
" father | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" school sex age address famsize Pstatus Medu Fedu Mjob Fjob \\\n",
"0 GP F 18 U GT3 A 4 4 at_home teacher \n",
"1 GP F 17 U GT3 T 1 1 at_home other \n",
"2 GP F 15 U LE3 T 1 1 at_home other \n",
"3 GP F 15 U GT3 T 4 2 health services \n",
"4 GP F 16 U GT3 T 3 3 other other \n",
"\n",
" reason guardian \n",
"0 course mother \n",
"1 course father \n",
"2 other mother \n",
"3 home mother \n",
"4 home father "
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Step 5. Create a lambda function that captalize strings."
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Step 6. Capitalize both Mjob and Fjob"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"0 TEACHER\n",
"1 OTHER\n",
"2 OTHER\n",
"3 SERVICES\n",
"4 OTHER\n",
"5 OTHER\n",
"6 OTHER\n",
"7 TEACHER\n",
"8 OTHER\n",
"9 OTHER\n",
"10 HEALTH\n",
"11 OTHER\n",
"12 SERVICES\n",
"13 OTHER\n",
"14 OTHER\n",
"15 OTHER\n",
"16 SERVICES\n",
"17 OTHER\n",
"18 SERVICES\n",
"19 OTHER\n",
"20 OTHER\n",
"21 HEALTH\n",
"22 OTHER\n",
"23 OTHER\n",
"24 HEALTH\n",
"25 SERVICES\n",
"26 OTHER\n",
"27 SERVICES\n",
"28 OTHER\n",
"29 TEACHER\n",
" ... \n",
"365 OTHER\n",
"366 SERVICES\n",
"367 SERVICES\n",
"368 SERVICES\n",
"369 TEACHER\n",
"370 SERVICES\n",
"371 SERVICES\n",
"372 AT_HOME\n",
"373 OTHER\n",
"374 OTHER\n",
"375 OTHER\n",
"376 OTHER\n",
"377 SERVICES\n",
"378 OTHER\n",
"379 OTHER\n",
"380 TEACHER\n",
"381 OTHER\n",
"382 SERVICES\n",
"383 SERVICES\n",
"384 OTHER\n",
"385 OTHER\n",
"386 AT_HOME\n",
"387 OTHER\n",
"388 SERVICES\n",
"389 OTHER\n",
"390 SERVICES\n",
"391 SERVICES\n",
"392 OTHER\n",
"393 OTHER\n",
"394 AT_HOME\n",
"Name: Fjob, dtype: object"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Step 7. Print the last elements of the data set."
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
\n",
" \n",
" \n",
" | \n",
" school | \n",
" sex | \n",
" age | \n",
" address | \n",
" famsize | \n",
" Pstatus | \n",
" Medu | \n",
" Fedu | \n",
" Mjob | \n",
" Fjob | \n",
" reason | \n",
" guardian | \n",
"
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" \n",
" \n",
" \n",
" 390 | \n",
" MS | \n",
" M | \n",
" 20 | \n",
" U | \n",
" LE3 | \n",
" A | \n",
" 2 | \n",
" 2 | \n",
" services | \n",
" services | \n",
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" other | \n",
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" 1 | \n",
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" course | \n",
" mother | \n",
"
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" M | \n",
" 21 | \n",
" R | \n",
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" 1 | \n",
" 1 | \n",
" other | \n",
" other | \n",
" course | \n",
" other | \n",
"
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" 393 | \n",
" MS | \n",
" M | \n",
" 18 | \n",
" R | \n",
" LE3 | \n",
" T | \n",
" 3 | \n",
" 2 | \n",
" services | \n",
" other | \n",
" course | \n",
" mother | \n",
"
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" \n",
" 394 | \n",
" MS | \n",
" M | \n",
" 19 | \n",
" U | \n",
" LE3 | \n",
" T | \n",
" 1 | \n",
" 1 | \n",
" other | \n",
" at_home | \n",
" course | \n",
" father | \n",
"
\n",
" \n",
"
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"
"
],
"text/plain": [
" school sex age address famsize Pstatus Medu Fedu Mjob Fjob \\\n",
"390 MS M 20 U LE3 A 2 2 services services \n",
"391 MS M 17 U LE3 T 3 1 services services \n",
"392 MS M 21 R GT3 T 1 1 other other \n",
"393 MS M 18 R LE3 T 3 2 services other \n",
"394 MS M 19 U LE3 T 1 1 other at_home \n",
"\n",
" reason guardian \n",
"390 course other \n",
"391 course mother \n",
"392 course other \n",
"393 course mother \n",
"394 course father "
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Step 8. Did you notice the original dataframe is still lowercase? Why is that? Fix it and captalize Mjob and Fjob."
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
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" \n",
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" | \n",
" school | \n",
" sex | \n",
" age | \n",
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" famsize | \n",
" Pstatus | \n",
" Medu | \n",
" Fedu | \n",
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" mother | \n",
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" AT_HOME | \n",
" course | \n",
" father | \n",
"
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" \n",
"
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"
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"text/plain": [
" school sex age address famsize Pstatus Medu Fedu Mjob Fjob \\\n",
"390 MS M 20 U LE3 A 2 2 SERVICES SERVICES \n",
"391 MS M 17 U LE3 T 3 1 SERVICES SERVICES \n",
"392 MS M 21 R GT3 T 1 1 OTHER OTHER \n",
"393 MS M 18 R LE3 T 3 2 SERVICES OTHER \n",
"394 MS M 19 U LE3 T 1 1 OTHER AT_HOME \n",
"\n",
" reason guardian \n",
"390 course other \n",
"391 course mother \n",
"392 course other \n",
"393 course mother \n",
"394 course father "
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Step 9. Create a function called majority that return a boolean value to a new column called legal_drinker"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"
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" \n",
" \n",
" | \n",
" school | \n",
" sex | \n",
" age | \n",
" address | \n",
" famsize | \n",
" Pstatus | \n",
" Medu | \n",
" Fedu | \n",
" Mjob | \n",
" Fjob | \n",
" reason | \n",
" guardian | \n",
" legal_drinker | \n",
"
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" other | \n",
" mother | \n",
" False | \n",
"
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" home | \n",
" mother | \n",
" False | \n",
"
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" 4 | \n",
" GP | \n",
" F | \n",
" 16 | \n",
" U | \n",
" GT3 | \n",
" T | \n",
" 3 | \n",
" 3 | \n",
" OTHER | \n",
" OTHER | \n",
" home | \n",
" father | \n",
" False | \n",
"
\n",
" \n",
"
\n",
"
"
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"text/plain": [
" school sex age address famsize Pstatus Medu Fedu Mjob Fjob \\\n",
"0 GP F 18 U GT3 A 4 4 AT_HOME TEACHER \n",
"1 GP F 17 U GT3 T 1 1 AT_HOME OTHER \n",
"2 GP F 15 U LE3 T 1 1 AT_HOME OTHER \n",
"3 GP F 15 U GT3 T 4 2 HEALTH SERVICES \n",
"4 GP F 16 U GT3 T 3 3 OTHER OTHER \n",
"\n",
" reason guardian legal_drinker \n",
"0 course mother True \n",
"1 course father False \n",
"2 other mother False \n",
"3 home mother False \n",
"4 home father False "
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Step 10. Multiply every number of the dataset by 10. \n",
"##### I know this makes no sense, don't forget it is just an exercise"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
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" famsize | \n",
" Pstatus | \n",
" Medu | \n",
" Fedu | \n",
" Mjob | \n",
" Fjob | \n",
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" HEALTH | \n",
" SERVICES | \n",
" home | \n",
" mother | \n",
" None | \n",
"
\n",
" \n",
" 4 | \n",
" GP | \n",
" F | \n",
" 160 | \n",
" U | \n",
" GT3 | \n",
" T | \n",
" 30 | \n",
" 30 | \n",
" OTHER | \n",
" OTHER | \n",
" home | \n",
" father | \n",
" None | \n",
"
\n",
" \n",
" 5 | \n",
" GP | \n",
" M | \n",
" 160 | \n",
" U | \n",
" LE3 | \n",
" T | \n",
" 40 | \n",
" 30 | \n",
" SERVICES | \n",
" OTHER | \n",
" reputation | \n",
" mother | \n",
" None | \n",
"
\n",
" \n",
" 6 | \n",
" GP | \n",
" M | \n",
" 160 | \n",
" U | \n",
" LE3 | \n",
" T | \n",
" 20 | \n",
" 20 | \n",
" OTHER | \n",
" OTHER | \n",
" home | \n",
" mother | \n",
" None | \n",
"
\n",
" \n",
" 7 | \n",
" GP | \n",
" F | \n",
" 170 | \n",
" U | \n",
" GT3 | \n",
" A | \n",
" 40 | \n",
" 40 | \n",
" OTHER | \n",
" TEACHER | \n",
" home | \n",
" mother | \n",
" None | \n",
"
\n",
" \n",
" 8 | \n",
" GP | \n",
" M | \n",
" 150 | \n",
" U | \n",
" LE3 | \n",
" A | \n",
" 30 | \n",
" 20 | \n",
" SERVICES | \n",
" OTHER | \n",
" home | \n",
" mother | \n",
" None | \n",
"
\n",
" \n",
" 9 | \n",
" GP | \n",
" M | \n",
" 150 | \n",
" U | \n",
" GT3 | \n",
" T | \n",
" 30 | \n",
" 40 | \n",
" OTHER | \n",
" OTHER | \n",
" home | \n",
" mother | \n",
" None | \n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" school sex age address famsize Pstatus Medu Fedu Mjob Fjob \\\n",
"0 GP F 180 U GT3 A 40 40 AT_HOME TEACHER \n",
"1 GP F 170 U GT3 T 10 10 AT_HOME OTHER \n",
"2 GP F 150 U LE3 T 10 10 AT_HOME OTHER \n",
"3 GP F 150 U GT3 T 40 20 HEALTH SERVICES \n",
"4 GP F 160 U GT3 T 30 30 OTHER OTHER \n",
"5 GP M 160 U LE3 T 40 30 SERVICES OTHER \n",
"6 GP M 160 U LE3 T 20 20 OTHER OTHER \n",
"7 GP F 170 U GT3 A 40 40 OTHER TEACHER \n",
"8 GP M 150 U LE3 A 30 20 SERVICES OTHER \n",
"9 GP M 150 U GT3 T 30 40 OTHER OTHER \n",
"\n",
" reason guardian legal_drinker \n",
"0 course mother None \n",
"1 course father None \n",
"2 other mother None \n",
"3 home mother None \n",
"4 home father None \n",
"5 reputation mother None \n",
"6 home mother None \n",
"7 home mother None \n",
"8 home mother None \n",
"9 home mother None "
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": []
}
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