pandas.date_range(start=None, end=None, periods=None, freq='D', tz=None, normalize=False, name=None, closed=None): This function creates a fixed frequency date-time index

pandas.isnull(obj): This function finds NaN and None values

pandas.merge(left, right, how='inner', on=None, left_on=None, right_on=None, left_index=False, right_index=False, sort=False, suffixes=('_x', '_y'), copy=True): This function merges the DataFrame objects with a database-like join on columns or indices

pandas.pivot_table(data, values=None, rows=None, cols=None, aggfunc='mean', fill_value=None, margins=False, dropna=True): This function creates a spreadsheet-like pivot table as a pandas DataFrame

pandas.read_csv(filepath_or_buffer, sep=',', dialect=None, compression=None, doublequote=True, escapechar=None, quotechar='"', quoting=0, skipinitialspace=False, lineterminator=None, header='infer', index_col=None, names=None, prefix=None, skiprows=None, skipfooter=None, skip_footer=0, na_values=None, na_fvalues=None, true_values=None, false_values=None, delimiter=None, converters=None, dtype=None, usecols=None, engine='c', delim_whitespace=False, as_recarray=False, na_filter=True, compact_ints=False, use_unsigned=False, low_memory=True, buffer_lines=None, warn_bad_lines=True, error_bad_lines=True, keep_default_na=True, thousands=Nment=None, decimal='.', parse_dates=False, keep_date_col=False, dayfirst=False, date_parser=None, memory_map=False, nrows=None, iterator=False, chunksize=None, verbose=False, encoding=None, squeeze=False, mangle_dupe_cols=True, tupleize_cols=False, infer_datetime_format=False): This function creates a DataFrame from a CSV file

pandas.read_excel(io, sheetname, **kwds): This function reads an Excel worksheet into a DataFrame

pandas.read_hdf(path_or_buf, key, **kwargs): This function returns a pandas object from an HDF store

pandas.read_json(path_or_buf=None, orient=None, typ='frame', dtype=True, convert_axes=True, convert_dates=True, keep_default_dates=True, numpy=False, precise_float=False, date_unit=None): This function creates a pandas object from a JSON string

pandas.to_datetime(arg, errors='ignore', dayfirst=False, utc=None, box=True, format=None, coerce=False, unit='ns', infer_datetime_format=False): This function converts a string or list of strings to datetime