Date Utils


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Documentation for package ‘dateutils’ version 0.1.5

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add_forecast_dates Add NA values to the tail of a wide data.table
agg_to_freq Aggregate long format data.table
agg_to_freq_wide Aggregate data.table and return wide format
allNA Are all elements 'NA'?
all_finite Rows with only finite values
any_finite Rows with finite values
can_seasonal Can data be seasonally adjusted?
col_to_list Convert columns to list
comp_form Companion Form
count_obs Count observations
day Return the day of a Date value
Diff Difference data
end_of_period End of period date
end_of_year End of Year
extract_basic_character Extract characters
extract_character Extract character values
extract_numeric Extract numeric values
fill_forward Fill Forward
first_of_month First of month
first_of_quarter First of Quarter
first_previous_quarter First of previous quarter date
fred Sample mixed frequency data from FRED
fredlib Library of metadata for mixed frequency dataset 'fred'
get_data_frq Get frequency of data based on missing observations
get_from_list Get from list
index_by_friday Find the Friday in a given week
is_in Find element of this_in that
last_in_month Last date in the month
last_in_quarter Last date in the week
last_in_week Last date in the week
last_in_year Last date in the year
last_obs Last observation
limit_character Limit Characters
long_run_var Long Run Variance of a VAR
match_index Match index values
match_ts_dates Match dates between two timeseries
mean_na Return the mean
month_days Number of days in a given month
number_finite Number of finite values in a column
numdum Dummies for Numeric Data
pct_chng Percent change
pct_response Percent of responses at a given frequency
process Process Data
process_MF Process mixed frequency
process_wide Process Wide Format Data
rollmax Rolling Max
rollmean Rolling mean
rollmin Rolling Min
row_to_list Convert rows to list
run_sa Seasonally adjust data using seas()
sd_na Return the standard deviation
seas_df_long Seasonally adjust long format data using seas()
seas_df_wide Seasonally adjust wide format data using seas()
spline_fill Spline fill missing observations
spline_fill_trend Spline fill missing observations
stack_obs Stack time series observations in VAR format
sum_na Return the sum
total_response Number of of responses at a given frequency
to_ts Tabular data to ts() format
try_detrend Remove low frequency trends from data
try_sa Seasonally adjust data using seas()
try_trend Estimate low frequnecy trends
ts_to_df ts() data to a dataframe