cheatsheet.ipynb

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    "# Cheatsheet\n",
    "\n",
    "```{admonition} Files\n",
    ":class: important\n",
    "You can {Download}`download cheatsheet as a pdf here<./cheatsheet.pdf>`.\n",
    "```\n",
    "\n",
    "## Resources\n",
    "[pandas API reference](https://pandas.pydata.org/docs/reference/index.html) \n",
    "\n",
    "[pandas User Guide](https://pandas.pydata.org/docs/user_guide/index.html)\n",
    "\n",
    "## Read and evaluate\n",
    "\n",
    "[`pd.read_csv()`](https://pandas.pydata.org/docs/reference/api/pandas.read_csv.html): Reads a CSV file into a DataFrame.\n",
    "\n",
    "[`df.head()`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.head.html): Returns the first n rows of the DataFrame.\n",
    "\n",
    "[`df.tail()`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.tail.html): Returns the last n rows of the DataFrame.\n",
    "\n",
    "[`df.columns`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.columns.html): Returns the column labels of the DataFrame.\n",
    "\n",
    "[`df.shape`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.shape.html): Returns a tuple (rows, columns) of the DataFrame.\n",
    "\n",
    "[`df.empty`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.empty.html): Indicates if the DataFrame is empty.\n",
    "\n",
    "[`df['title'].unique()`](https://pandas.pydata.org/docs/reference/api/pandas.Series.unique.html): Returns unique values of Series.\n",
    "\n",
    "[`df['title'].value_counts()`](https://pandas.pydata.org/docs/reference/api/pandas.Series.value_counts.html): Returns Series containing counts of unique value in column (example ’title’).\n",
    "\n",
    "## Access rows, columns, and cells\n",
    "\n",
    "[`df['title']`](https://pandas.pydata.org/docs/getting_started/intro_tutorials/03_subset_data.html)or [`df.title`](https://pandas.pydata.org/docs/getting_started/intro_tutorials/03_subset_data.html): Select single column with specific name (example ‘title’).\n",
    "\n",
    "[`df.loc[]`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.loc.html): Access rows & columns by label(s) or a boolean array.\n",
    "\n",
    "[`df.iloc[]`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.loc.html): Purely integer-location based indexing for selection by position.\n",
    "\n",
    "[`df.iat[1, 2]`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.iat.html?highlight=iat): Access single value by index.\n",
    "\n",
    "[`df.at[4, 'A']`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.at.html?highlight=): Access single value by label.\n",
    "\n",
    "\n",
    "## Clean up\n",
    "\n",
    "[`pd.isna()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.isna.html): Detects missing values.\n",
    "\n",
    "[`pd.notna()`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.notna.html): Detects non-missing values.\n",
    "\n",
    "[`df.dropna()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.dropna.html): Removes missing values from the DataFrame.\n",
    "\n",
    "[`df.duplicated()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.duplicated.html): Returns boolean Series of duplicate rows.\n",
    "\n",
    "[`df.drop_duplicates()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.drop_duplicates.html): Removes duplicate rows from DataFrame.\n",
    "\n",
    "[`Series.apply()`](https://pandas.pydata.org/docs/reference/api/pandas.Series.apply.html): Invoke function on values of Series.\n",
    "\n",
    "[`Series.str.rstrip()`](https://pandas.pydata.org/docs/reference/api/pandas.Series.str.rstrip.html): Removes trailing characters.\n",
    "\n",
    "[`Series.str.zfill()`](https://pandas.pydata.org/docs/reference/api/pandas.Series.str.zfill.html): Pads Series with zeros.\n",
    "\n",
    "[`Series.str.strip()`](https://pandas.pydata.org/docs/reference/index.html): Strips whitespaces from Series.\n",
    "\n",
    "## Loop through rows\n",
    "\n",
    "[`df.iterrows()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.iterrows.html): Loops through DataFrame rows as (index, Series) pairs.\n",
    "\n",
    "## Merge DataFrames\n",
    "\n",
    "[`pd.merge()`](https://pandas.pydata.org/docs/reference/api/pandas.merge.html) : Merge DataFrame or named Series objects with a database-style join.\n",
    "\n",
    "`how=“left”` : Merges on all ids from left DataFrame. Ids not in left DataFrame will not be included.\n",
    "\n",
    "`how=“right”` : Merges on all ids from right DataFrame. Ids not in right DataFrame will not be included.\n",
    "\n",
    "`how=”outer”` : Merges on all ids from both DataFrames.\n",
    "\n",
    "`how=“inner”` : Merges only on ids found in both DataFrames. Ids found in only one DataFrame will not be included.\n",
    "\n",
    "## Reshaping\n",
    "\n",
    "[`df.explode()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.explode.html): Transforms each element of a list-like to a row, replicating index values.\n",
    "\n",
    "[`df.pivot()`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.pivot.html): Reshape data (produce a “pivot” table) based on column values.\n",
    "\n",
    "[`df.pivot_table()`](https://pandas.pydata.org/docs/reference/api/pandas.pivot_table.html): Create a spreadsheet-style pivot table as a DataFrame.\n",
    "\n",
    "[`lambda`](https://docs.python.org/3/tutorial/controlflow.html): An anonymous (unnamed) function that applies arguments to various parameters and returns an expression (outcome).\n",
    "\n",
    "[`df.melt()`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.melt.html): Unpivot a DataFrame from wide to long format, optionally leaving identifiers set.\n",
    "\n",
    "## Sort DataFrame\n",
    "\n",
    "[`df.sort_values()`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.sort_values.html): Sort by the values along either axis.\n",
    "\n",
    "## Create new CSV\n",
    "\n",
    "[`df.to_csv()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_csv.html): Writes the DataFrame to a CSV file"
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