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Merge pull request #67 from UBC-MDS/final_changes
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fixed a small grammatical error
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stephqwu authored Jan 26, 2025
2 parents 76f0d1f + 2443017 commit 1627b7c
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45 changes: 0 additions & 45 deletions docs/example.ipynb

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14 changes: 7 additions & 7 deletions docs/summarize.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"Imagine you are working on a data science problem and you have got a dataset that you should extract interesting patterns from. The time is limited, thus you think of a convenient function that could the initial exploratory data analysis for you - generate a quick summary of the dataset at hand. It could then compile the information into a well-organized PDF report, complete with charts and tables, enabling the team to quickly grasp trends and have a quick discussion - all without needing to manually process the data. \n",
"Imagine you are working on a data science problem and you have got a dataset that you should extract interesting patterns from. The time is limited, thus you think of a convenient function that could do the initial exploratory data analysis for you generate a quick summary of the dataset at hand. It could then compile the information into a well-organized PDF report, complete with charts and tables, enabling the team to quickly grasp trends and have a quick discussion all without the need to manually process the data. \n",
"\n",
"Situations like this call for the function `summarize` from the `summarease` package."
]
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"cell_type": "markdown",
"metadata": {},
"source": [
"#### Importing the necessary functions and libraries"
"### Importing the necessary functions and libraries"
]
},
{
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"cell_type": "markdown",
"metadata": {},
"source": [
"#### Step 1 - Load the dataset"
"### Step 1 - Load the dataset"
]
},
{
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"cell_type": "markdown",
"metadata": {},
"source": [
"#### Step 2 - Prepare the dataset information (optional)"
"### Step 2 - Prepare the dataset information (optional)"
]
},
{
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"cell_type": "markdown",
"metadata": {},
"source": [
"#### Step 3 - Run the summarize function"
"### Step 3 - Run the summarize function"
]
},
{
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"cell_type": "markdown",
"metadata": {},
"source": [
"##### Using plots"
"#### Using plots"
]
},
{
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"cell_type": "markdown",
"metadata": {},
"source": [
"##### Using tables"
"#### Using tables"
]
},
{
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10 changes: 7 additions & 3 deletions docs/summarize_dtypes.ipynb
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"\n",
"### Function Output\n",
"\n",
"The function returns a pandas DataFrame summarizing the counts of each data type in the dataset.\n",
"\n",
"\n",
"The function returns a pandas DataFrame summarizing the counts of each data type in the dataset."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Necessary libraries\n",
"\n",
"To use the `summarize_dtypes_table` function, ensure the following libraries are installed:"
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8 changes: 4 additions & 4 deletions docs/summarize_numeric.ipynb
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"\n",
"We'll use the following dataset to demonstrate the module's functionality:\n",
"\n",
"#### Dataset: Numeric Data"
"### Dataset: Numeric Data"
]
},
{
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"source": [
"## Example usage\n",
"\n",
"#### `summarize_numeric`\n",
"### `summarize_numeric`\n",
"\n",
"This function calculates summary statistics or generates visualizations for numeric columns. It takes two parameters:\n",
"\n",
"\n",
"- `dataset`: The input dataset containing numeric variables. It must be a DataFrame.\n",
"- `summarize_by`: Specifies the format for summarizing the numeric variables. It can be either `\"table\"` (default) to generate a summary table, or `\"plot\"` to generate visualizations like density plots and a correlation heatmap.\n",
"\n",
"##### Example 1: Summarizing with a Table"
"#### Example 1: Summarizing with a Table"
]
},
{
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"cell_type": "markdown",
"metadata": {},
"source": [
"##### Example 2: Visualizing Numeric Relationships"
"#### Example 2: Visualizing Numeric Relationships"
]
},
{
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12 changes: 6 additions & 6 deletions docs/summarize_target.ipynb
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"cell_type": "markdown",
"metadata": {},
"source": [
"## Example dataset\n",
"## Example datasets\n",
"\n",
"We'll use the following datasets to demonstrate the module's functionality:\n",
"\n",
"#### Dataset 1: Categorical Target Dataset"
"### Dataset 1: Categorical Target Dataset"
]
},
{
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"cell_type": "markdown",
"metadata": {},
"source": [
"#### Dataset 2: Numerical Target Dataset"
"### Dataset 2: Numerical Target Dataset"
]
},
{
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"cell_type": "markdown",
"metadata": {},
"source": [
"##### Example 1: Summarizing a Categorical Target using a table"
"#### Example 1: Summarizing a Categorical Target using a table"
]
},
{
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"cell_type": "markdown",
"metadata": {},
"source": [
"##### Example 2: Summarizing a Numerical Target"
"#### Example 2: Summarizing a Numerical Target"
]
},
{
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"cell_type": "markdown",
"metadata": {},
"source": [
"##### Example: Visualizing Class Balance"
"#### Example 3: Visualizing Class Balance"
]
},
{
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