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Exercise.ipynb
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"metadata": {},
"cell_type": "markdown",
"source": "# Fictional Army - Filtering and Sorting"
},
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"metadata": {},
"cell_type": "markdown",
"source": "### Step 1. Import the necessary libraries"
},
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"trusted": true
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"cell_type": "code",
"source": "",
"execution_count": 3,
"outputs": []
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"metadata": {},
"cell_type": "markdown",
"source": "### Step 2. This is the data given as a dictionary"
},
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"source": "# Create an example dataframe about a fictional army\nraw_data = {'regiment': ['Nighthawks', 'Nighthawks', 'Nighthawks', 'Nighthawks', 'Dragoons', 'Dragoons', 'Dragoons', 'Dragoons', 'Scouts', 'Scouts', 'Scouts', 'Scouts'],\n 'company': ['1st', '1st', '2nd', '2nd', '1st', '1st', '2nd', '2nd','1st', '1st', '2nd', '2nd'],\n 'deaths': [523, 52, 25, 616, 43, 234, 523, 62, 62, 73, 37, 35],\n 'battles': [5, 42, 2, 2, 4, 7, 8, 3, 4, 7, 8, 9],\n 'size': [1045, 957, 1099, 1400, 1592, 1006, 987, 849, 973, 1005, 1099, 1523],\n 'veterans': [1, 5, 62, 26, 73, 37, 949, 48, 48, 435, 63, 345],\n 'readiness': [1, 2, 3, 3, 2, 1, 2, 3, 2, 1, 2, 3],\n 'armored': [1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1],\n 'deserters': [4, 24, 31, 2, 3, 4, 24, 31, 2, 3, 2, 3],\n 'origin': ['Arizona', 'California', 'Texas', 'Florida', 'Maine', 'Iowa', 'Alaska', 'Washington', 'Oregon', 'Wyoming', 'Louisana', 'Georgia']}",
"execution_count": 4,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Step 3. Create a dataframe and assign it to a variable called army. \n\n#### Don't forget to include the columns names"
},
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"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
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{
"metadata": {},
"cell_type": "markdown",
"source": "### Step 4. Set the 'origin' colum as the index of the dataframe"
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"execution_count": null,
"outputs": []
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"metadata": {},
"cell_type": "markdown",
"source": "### Step 5. Print only the column veterans"
},
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"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Step 6. Print the columns 'veterans' and 'deaths'"
},
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"cell_type": "code",
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"execution_count": null,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Step 7. Print the name of all the columns."
},
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"metadata": {
"trusted": true
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"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Step 8. Select the 'deaths', 'size' and 'deserters' columns from Maine and Alaska"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Step 9. Select the rows 3 to 7 and the columns 3 to 6"
},
{
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"trusted": true
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"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
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{
"metadata": {},
"cell_type": "markdown",
"source": "### Step 10. Select every row after the fourth row"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Step 11. Select every row up to the 4th row"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Step 12. Select the 3rd column up to the 7th column"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Step 13. Select rows where 'deaths' is greater than 50"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Step 14. Select rows where 'deaths' is greater than 500 or less than 50"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Step 15. Select all the regiments not named 'Dragoons'"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Step 16. Select the rows called Texas and Arizona"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Step 17. Select the third cell in the row named Arizona"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Step 18. Select the third cell down in the column named deaths"
},
{
"metadata": {
"trusted": true
},
"cell_type": "code",
"source": "",
"execution_count": null,
"outputs": []
}
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