Deprecated pandas updates, configparser imports

• Updated functions to latest pandas versions in place of deprecated versions
• Required configparser backport in setup.py only for Python 2.7 and 3.4
• Removed explicit backport namespace from configparser import statement in configparser_read.py
• Changed variable names to avoid shadowing 'id' variable

Updates to daily observation and consecutive days count functions

• Added parameter include_first_and_last_days=False to consecutive_days_of_observations()
• Renamed daily_cycle_and_temp_obs_counts function to daily_cycle_sensor_and_geospatial_obs_counts
• Name variable names in test files consistent by replacing inside to sensor_obs and outside to geosptial_obs, to be more general

Timeseries module updates

• ID and start/end arguments now optional in timeseries module functions (default to selecting all records)
• Optional ID and start/end arguments are keyword arguments instead of positional arguments
• Cycling device IDs and sensor IDs are independent parameters in timeseries module
• More general data category names for named tuple records in dicts and functions (Sensors, Geospatial)
• Sensor and geospatial data in timeseries module can be vectors or, as in previous releases, scalars

3.1.1-beta

Fixed function to make it general for all data types in support of future API

Time series multiple column selection option

• Added cols= parameter to temps_arr_by_freq in timeseries module for selecting column(s) by label

3.0.1-beta

• Index column detection fix

DataFrame indexing and formatting improvements and creation speed-up

• Added new parameters to pickle and dict creation functions for specifying ID or cycle mode column headings
• Made int, float and datetime.datetime conversion from strings part of pickle/dict creation
• Added column metadata to pickled dicts and dicts, pairing them and records dict within overall dict
• Made DataFrames retain original column headings from text files across all index and data columns
• Added cols_to_ignore, which takes either string or integer arguments
• Added df_select_datetime_range function for slicing DataFrames
• Added cycle mode to MultiIndex in cycling records and DataFrames

Import detect_columns() with __init__

2.0.1-beta

Import detect_columns

Separate metadata detection summary

detect_columns() takes the same arguments as dict_from_file() and pickle_from_file(), plus the 'meta'=True argument in order to return column metadata in a dict, without records.

Column meta-data and expanded delimiter/quote options

Row text delimiters may be specified by the user. (By default, commas, tabs, pipes and spaces are automatically detected, in that priority order). In addition, the user can indicate characters that surround the data fields and that should be removed. Double and single quotes are automatically detected and removed by default.

strftime= keyword argument can take string to specify unusual datetime formats, if dateutil is not able to infer it automatically.