def clean_nan_values(move_data, axis=0, how='any', thresh=None, subset=None,
    inplace=False):
    """
    Removes missing values from the dataframe.

    Parameters
    ----------
    move_data : dataframe
        The input trajectory data
    axis : Integer or String (default 0)
        Determines if rows or columns that contain missing values are removed. If set to 0 or "index",
        the function drops the rows containing the missing value.
        If set to 1 or "columns", drops the columns containing the missing value.
    how : String, optional (default "any")
        Determines if a row or column is droped for having at least one NA value or all value NA.
        If set to "any", the rows or columns will be droped, if it has any NA values.
        If set to "all", the rows or columns will be droped, if all of it"s values are NA.
    thresh : Integer, optional (None by default)
        Minimum non-NA required value to avoid dropping
    subset : array of String
        Indicates the labels along the other axis to consider. E.g. if you want to drop columns,
        subset would indicate a list of rows to be included.
    inplace : boolean, default(False by default)
        if set to true the operation is done in place, the original dataframe will be altered and None is returned.

    Returns
    -------
    move_data : dataframe or None
        The filtered trajectories without nan values.
    """
    return move_data.dropna(axis=axis, how=how, thresh=thresh, subset=
        subset, inplace=inplace)
