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Update advanced notebooks
Fix typos
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‎2_Advanced/01_Pandas_Accessing_Data.ipynb

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‎2_Advanced/02_Pandas_Data_Cleaning.ipynb

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"\n",
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"#### Notes\n",
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"\n",
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"- `df.fillna()`: Fill missing values.\n",
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"- `df.fillna()`: Fill missing values\n",
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"\n",
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"#### Examples\n",
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"\n",

‎2_Advanced/03_Pandas_Data_Management.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Let's fill in missing values with the median value"
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"Let's fill in missing values with the median value."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Now let's inspect the altered dataframe."
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"Now let's inspect the altered DataFrame."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Well both the variables of `df_original` and `df_altered` are referencing the same dataframe."
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"Well both the variables of `df_original` and `df_altered` are referencing the same DataFrame."
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]
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},
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‎2_Advanced/05_Pandas_Index_Management.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Let's look at our dataframe:"
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"Let's look at our DataFrame."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Let's inspect our index"
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"Let's inspect our index."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"It has no name... so let's name it"
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"It has no name... so let's name it."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Inspecting it"
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"Inspecting it."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Index is no longer correctly spaced by 1 increment"
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"Index is no longer correctly spaced by 1 increment."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Technically we could `.drop()` the `job_index`\n",
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"Technically we could `.drop()` the `job_index`.\n",
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"\n",
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"BUT, if we wanted to do some sort of merge operations in the future with our original dataframe, this provides the unique id to do that"
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"BUT, if we wanted to do some sort of merge operations in the future with our original DataFrame, this provides the unique `id` to do that."
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]
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{
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"\n",
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"### Notes \n",
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"\n",
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"* `sort_index()`: Sorts the DataFrame by the index (row labels), either ascending or descending. This helps in quickly organizing data by the index and is often used after set_index()."
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"* `sort_index()`: Sorts the DataFrame by the index (row labels), either ascending or descending. This helps in quickly organizing data by the index and is often used after `set_index()`."
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]
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},
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{
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"source": [
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"### Example\n",
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"\n",
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"Back to our pivoted dataframe let's sort this new index alphabetically"
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"Back to our pivoted DataFrame let's sort this new index alphabetically."
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]
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},
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{

‎2_Advanced/06_Exercise_Job_Demand.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"4. Let's sort this"
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"4. Let's sort this."
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]
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Instead we'll just focus on the top 3 roles"
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"Instead we'll just focus on the top 3 roles."
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]
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},
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{

‎2_Advanced/07_Pandas_Merge_DataFrames.ipynb

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"## Notes\n",
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"\n",
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"* `merge()`: Combine DataFrames based on common columns or indices, similar to SQL joins (inner, outer, left, right).\n",
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"* It merges rows from the DataFrame based on the specific keys\n",
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"* It merges rows from the DataFrame based on the specific keys.\n",
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"\n",
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"## Examples"
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]
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"source": [
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"### Example 1\n",
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"\n",
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"We need to combine two dataframes:\n",
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"- `df_jobs` has info similiar to our `df` dataframe\n",
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"We need to combine two DataFrames:\n",
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"- `df_jobs` has info similiar to our `df` DataFrame\n",
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"- `df_companies` has company info"
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]
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},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Let's make some fake data for this\n",
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"Let's make some fake data for this.\n",
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"\n",
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"**NOTE: The code here is not important for you to understand**"
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"**NOTE: The code here is not important for you to understand**."
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]
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},
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{

‎2_Advanced/08_Pandas_Concat_DataFrames.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"3. Concatenate the first quarter"
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"3. Concatenate the first quarter."
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]
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"4. Inspecting to confirm"
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"4. Inspecting to confirm."
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]
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},
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{

‎2_Advanced/09_Pandas_Exporting_Data.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Another popular form to export to for your non code savy friends is to excel:"
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"Another popular form to export to for your non code savy friends is to Excel:"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Now we can save our jobs to a csv"
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"Now we can save our jobs to a csv."
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]
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{

‎2_Advanced/10_Pandas_Applying_Functions.ipynb

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"source": [
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"### Example 1\n",
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"\n",
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"Calculate projected salaries next year, using an assumed rate of 3.0% for all roles"
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"Calculate projected salaries next year, using an assumed rate of 3.0% for all roles."
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]
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"We can actually simplify this with a lambda function"
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"We can actually simplify this with a lambda function."
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Let's look at the `literal_eval()` fucntion from the Python Standard Library `ast` module"
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"Let's look at the `literal_eval()` function from the Python Standard Library `ast` module."
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]
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{

‎2_Advanced/11_Pandas_Explode.ipynb

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"cell_type": "markdown",
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"source": [
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"3. We'll `reset_index` to transform skills_count from a Series to a DataFrame"
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"3. We'll `reset_index` to transform skills_count from a Series to a DataFrame."
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"4. We'll prep for plotting by the data getting in descending order"
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"4. We'll prep for plotting by the data getting in descending order."
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‎2_Advanced/12_Exercise_Trending_Skills.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"3. Explode the `job_skills` column"
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"3. Explode the `job_skills` column."
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"5. (Optional) I like to have my months as names, not numbers, so let's change this"
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"5. (Optional) I like to have my months as names, not numbers, so let's change this."
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]
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"6. Let's graph the top 5 skills by count"
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"6. Let's graph the top 5 skills by count."
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‎2_Advanced/13_Matplotlib_Format_Charts.ipynb

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"\n",
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"* `subplots()`: Create multiple plots within a single figure. \n",
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"* Returns two objects: \n",
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" 1. `fig` - represents the entire figure window that will contain all of the subplots\n",
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" 2. `ax` - either a single axis object (for a single subplot) or an array of axis objects (for multiple subplots)\n",
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" 1. `fig` - represents the entire figure window that will contain all the subplots.\n",
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" 2. `ax` - either a single axis object (for a single subplot) or an array of axis objects (for multiple subplots).\n",
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"* Arguments:\n",
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" * `nrows` and `ncols` determine the number of rows and columns of subplots, respectively.\n",
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" * `sharex` and `sharey` control whether the x-axes or y-axes should be shared among subplots.\n",
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Let's add two plots"
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"Let's add two plots."
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"cell_type": "markdown",
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"source": [
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"Alternatively, we can plot how Matplotlib intended"
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"Alternatively, we can plot how Matplotlib intended."
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"source": [
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"### Examples\n",
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"\n",
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"Create a subplot that displays individual bar charts for each `job_title_short` from the DataFrame we created in `11_Pandas_Explode`\n",
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"Create a subplot that displays individual bar charts for each `job_title_short` from the DataFrame we created in `11_Pandas_Explode`.\n",
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"\n",
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"Note: This DataFrame \n",
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"Note: This DataFrame.\n",
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"\n",
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"Here's the code from our last exercise:"
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Plot these top jobs on the same plot"
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"Plot these top jobs on the same plot."
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‎2_Advanced/15_Matplotlib_Scatter_Plots.ipynb

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"* `text`: Add text annotations to the plot.\n",
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"#### Common Arguments\n",
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"* `x`: The x-coordinate for the text.\n",
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"* `y`: The y-coordinate for the text.\n",
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"* `s`: The text to display.\n",
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"* `fontsize`: The font size of the text.\n",
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"* `color`: The color of the text.\n",
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"* `ha`: Horizontal alignment of the text.\n",
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"* `va`: Vertical alignment of the text."
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"* `x`: The x-coordinate for the text\n",
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"* `y`: The y-coordinate for the text\n",
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"* `s`: The text to display\n",
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"* `fontsize`: The font size of the text\n",
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"* `color`: The color of the text\n",
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"* `ha`: Horizontal alignment of the text\n",
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"* `va`: Vertical alignment of the text"
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]
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},
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{

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