A table listing some commonly used pandas functions along with their descriptions:

Function Name	Description
`pandas.DataFrame()`	Creates a new DataFrame, a two-dimensional labeled data structure with columns of potentially different types.
`pandas.Series()`	Creates a new Series, a one-dimensional labeled array capable of holding any data type.
`DataFrame.head()`	Returns the first n rows of a DataFrame. Default value of n is 5.
`DataFrame.tail()`	Returns the last n rows of a DataFrame. Default value of n is 5.
`DataFrame.shape`	Returns a tuple representing the dimensions of the DataFrame (rows, columns).
`DataFrame.info()`	Prints a concise summary of a DataFrame, including the data types and memory usage.
`DataFrame.describe()`	Show descriptive statistics of the DataFrame, such as count, mean, min, max, etc.
`DataFrame.columns`	Returns the column labels of the DataFrame.
`DataFrame.index`	Returns the index (row labels) of the DataFrame.
`DataFrame.loc[]`	Accesses a group of rows and columns by label(s) or a boolean array.
`DataFrame.iloc[]`	Accesses a group of rows and columns by integer-based position(s).
`DataFrame.drop()`	Removes specified rows or columns from a DataFrame.
`DataFrame.isnull()`	Checks for missing values in the DataFrame and returns a boolean mask.
`DataFrame.fillna()`	Fills missing values in the DataFrame with a specified value or method.
`DataFrame.idxmax()`	Returns the index of the row with the highest value in the specified column.
`DataFrame.idxmin()`	Returns the index of the row with the lowest value in the specified column.
`DataFrame.sort_values()`	Sorts the DataFrame by the values in a specified column.
`DataFrame.rename()`	Renames the index labels or column names of a DataFrame.
`DataFrame.drop_duplicates()`	Removes duplicate rows from a DataFrame.
`DataFrame.concat()`	Concatenates two or more DataFrames into a single DataFrame.
`DataFrame.merge()`	Merges two DataFrames on a specified column.
`DataFrame.plot()`	Creates a plot of the specified column(s) of a DataFrame.
`DataFrame.groupby()`	Creates a group that can be used to group a DataFrame by a specified column.
`DataFrame.agg()`	Aggregates data from a DataFrame.
`DataFrame.pivot_table()`	Creates a pivot table that groups and aggregates data from a DataFrame.
`DataFrame.melt()`	Converts a DataFrame from wide to long format.
`DataFrame.stack()`	Converts a DataFrame from wide to long format, stacking all columns into a single column.
`DataFrame.unstack()`	Converts a DataFrame from long to wide format, unstacking a single column into multiple columns.
`pandas.crosstab()`	Creates a two-way table that can show the frequency counts of multiple columns.

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