Glossary
Glossary
Embedded Files
Glossary
Glossary
Below is the summary of all the functions and methods that you learned in this lesson:
Below is the summary of all the functions and methods that you learned in this lesson:
Category: Initialization and Utility
Category: Initialization and Utility
Reads a comma-separated values (csv) file present at relative_path_to_file and loads it as a DataFrame
Reads a comma-separated values (csv) file present at relative_path_to_file and loads it as a DataFrame
Returns a 2-D heterogeneous tabular data. Note: There are other optional arguments as well that you can use to create a dataframe.
Returns a 2-D heterogeneous tabular data. Note: There are other optional arguments as well that you can use to create a dataframe.
Returns 1-D ndarray with axis labels
Returns 1-D ndarray with axis labels
pandas.Series.shape
pandas.Series.shape
pandas.DataFrame.shape
pandas.DataFrame.shape
Returns a tuple representing the dimensions
Returns a tuple representing the dimensions
pandas.Series.ndim
pandas.Series.ndim
pandas.DataFrame.ndim
pandas.DataFrame.ndim
Returns the number of the dimensions (rank). It will return 1 in case of a Series
Returns the number of the dimensions (rank). It will return 1 in case of a Series
pandas.Series.size
pandas.Series.size
pandas.DataFrame.size
pandas.DataFrame.size
Returns the number of elements
Returns the number of elements
pandas.Series.values
pandas.Series.values
Returns the data available in the Series
Returns the data available in the Series
pandas.Series.index
pandas.Series.index
Returns the indexes available in the Series
Returns the indexes available in the Series
Returns a same sized object having True for NaN elements and False otherwise.
Returns a same sized object having True for NaN elements and False otherwise.
Returns the count of non-NaN values along the given axis. If axis=0, it will count down the dataframe, meaning column-wise count of non-NaN values.
Returns the count of non-NaN values along the given axis. If axis=0, it will count down the dataframe, meaning column-wise count of non-NaN values.
Return the first n rows from the dataframe. By default, n=5.
Return the first n rows from the dataframe. By default, n=5.
Return the last n rows from the dataframe. By default, n=5. Supports negative indexing as well.
Return the last n rows from the dataframe. By default, n=5. Supports negative indexing as well.
Generate the descriptive statistics, such as, count, mean, std deviation, min, and max.
Generate the descriptive statistics, such as, count, mean, std deviation, min, and max.
Returns the minimum of the values along the given axis.
Returns the minimum of the values along the given axis.
Returns the maximum of the values along the given axis.
Returns the maximum of the values along the given axis.
Returns the mean of the values along the given axis.
Returns the mean of the values along the given axis.
Compute pairwise correlation of columns, excluding NA/null values.
Compute pairwise correlation of columns, excluding NA/null values.
Provide rolling window calculation, such as pandas.DataFrame.rolling(15).mean() for rolling mean over window size of 15.
Provide rolling window calculation, such as pandas.DataFrame.rolling(15).mean() for rolling mean over window size of 15.
Access a group of rows and columns by label(s)
Access a group of rows and columns by label(s)
Groups the dataframe using a given mapper function or or by a Series of columns.
Groups the dataframe using a given mapper function or or by a Series of columns.
Category: Manipulation
Category: Manipulation
Drops the element positioned at the given index(es)
Drops the element positioned at the given index(es)
Drop specified labels (entire columns or rows) from the dataframe.
Drop specified labels (entire columns or rows) from the dataframe.
Return the item and drop it from the frame. If not found, then raise a KeyError.
Return the item and drop it from the frame. If not found, then raise a KeyError.
Insert column having given values into DataFrame at specified location.
Insert column having given values into DataFrame at specified location.
Rename label(s) (columns or row-indexes) as mentioned in the dictionary-like
Rename label(s) (columns or row-indexes) as mentioned in the dictionary-like
Set the DataFrame's row-indexes using existing column-values.
Set the DataFrame's row-indexes using existing column-values.
Remove rows (if axis=0) or columns (if axis=1) that contain missing values.
Remove rows (if axis=0) or columns (if axis=1) that contain missing values.
Replace NaN values with the specified value along the given axis, and using the given method (‘backfill’, ‘bfill’, ‘pad’, ‘ffill’, None)
Replace NaN values with the specified value along the given axis, and using the given method (‘backfill’, ‘bfill’, ‘pad’, ‘ffill’, None)
Replace the NaN values with the estimated value calculated using the given method along the given axis.
Replace the NaN values with the estimated value calculated using the given method along the given axis.
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