Example #1
0
def check_if_data_exists_at_less_aggregated_geoscale(df, geoscale,
                                                     activityname):
    """
    In the event data does not exist at specified geoscale,
    check if data exists at less aggregated level
    :param df: Either flowbyactivity or flowbysector dataframe
    :param geoscale: national, state, or county
    :param activityname: str, activity col names to check
    :return: str, geoscale to use
    """

    if geoscale == 'national':
        df = df[(df[fba_activity_fields[0]] == activityname) |
                (df[fba_activity_fields[1]] == activityname)]
        fips = create_geoscale_list(df, 'state')
        df = df[df['Location'].isin(fips)]
        if len(df) == 0:
            vLog.info("No flows found for %s at the state scale", activityname)
            fips = create_geoscale_list(df, 'county')
            df = df[df['Location'].isin(fips)]
            if len(df) == 0:
                vLog.info("No flows found for %s at the county scale",
                          activityname)
            else:
                vLog.info(
                    "Flow-By-Activity data exists for %s at "
                    "the county level", activityname)
                new_geoscale_to_use = 'county'
                return new_geoscale_to_use
        else:
            vLog.info(
                "Flow-By-Activity data exists for %s at "
                "the state level", activityname)
            new_geoscale_to_use = 'state'
            return new_geoscale_to_use
    if geoscale == 'state':
        df = df[(df[fba_activity_fields[0]] == activityname) |
                (df[fba_activity_fields[1]] == activityname)]
        fips = create_geoscale_list(df, 'county')
        df = df[df['Location'].isin(fips)]
        if len(df) == 0:
            vLog.info("No flows found for %s at the "
                      "county scale", activityname)
        else:
            vLog.info(
                "Flow-By-Activity data exists for %s "
                "at the county level", activityname)
            new_geoscale_to_use = 'county'
            return new_geoscale_to_use
Example #2
0
def check_if_data_exists_at_less_aggregated_geoscale(df, geoscale,
                                                     activityname):
    """
    In the event data does not exist at specified geoscale, check if data exists at less aggregated level
    :param df: Either flowbyactivity or flowbysector dataframe
    :param data_to_check: Either an activity name (ex. 'Domestic') or a sector (ex. '1124')
    :param geoscale: national, state, or county
    :param flowbytype: 'fba' for flowbyactivity, 'fbs' for flowbysector
    :return:
    """

    if geoscale == 'national':
        df = df[(df[fba_activity_fields[0]] == activityname) |
                (df[fba_activity_fields[1]] == activityname)]
        fips = create_geoscale_list(df, 'state')
        df = df[df['Location'].isin(fips)]
        if len(df) == 0:
            log.info("No flows found for " + activityname +
                     "  at the state scale.")
            fips = create_geoscale_list(df, 'county')
            df = df[df['Location'].isin(fips)]
            if len(df) == 0:
                log.info("No flows found for " + activityname +
                         "  at the county scale.")
            else:
                log.info("Flowbyactivity data exists for " + activityname +
                         " at the county level")
                new_geoscale_to_use = 'county'
                return new_geoscale_to_use
        else:
            log.info("Flowbyactivity data exists for " + activityname +
                     " at the state level")
            new_geoscale_to_use = 'state'
            return new_geoscale_to_use
    if geoscale == 'state':
        df = df[(df[fba_activity_fields[0]] == activityname) |
                (df[fba_activity_fields[1]] == activityname)]
        fips = create_geoscale_list(df, 'county')
        df = df[df['Location'].isin(fips)]
        if len(df) == 0:
            log.info("No flows found for " + activityname +
                     "  at the county scale.")
        else:
            log.info("Flowbyactivity data exists for " + activityname +
                     " at the county level")
            new_geoscale_to_use = 'county'
            return new_geoscale_to_use
Example #3
0
def check_if_data_exists_at_geoscale(df, geoscale, activitynames='All'):
    """
    Check if an activity or a sector exists at the specified geoscale
    :param df: flowbyactivity dataframe
    :param activitynames: Either an activity name (ex. 'Domestic')
        or a sector (ex. '1124')
    :param geoscale: national, state, or county
    :return: str, 'yes' or 'no'
    """

    # if any activity name is specified, check if activity data
    # exists at the specified geoscale
    activity_list = []
    if activitynames != 'All':
        if isinstance(activitynames, str):
            activity_list.append(activitynames)
        else:
            activity_list = activitynames
        # check for specified activity name
        df = df[(df[fba_activity_fields[0]].isin(activity_list)) |
                (df[fba_activity_fields[1]].isin(activity_list))].reset_index(
                    drop=True)
    else:
        activity_list.append('activities')

    # filter by geoscale depends on Location System
    fips = create_geoscale_list(df, geoscale)

    df = df[df['Location'].isin(fips)]

    if len(df) == 0:
        vLog.info("No flows found for %s at the %s scale",
                  ', '.join(activity_list), geoscale)
        exists = "No"
    else:
        vLog.info("Flows found for %s at the %s scale",
                  ', '.join(activity_list), geoscale)
        exists = "Yes"

    return exists