diff --git a/dev/apply/index.html b/dev/apply/index.html index ee83e033..afc9b127 100644 --- a/dev/apply/index.html +++ b/dev/apply/index.html @@ -122,11 +122,11 @@ │ 2001-12-26 │ 21.065 │ │ 2001-12-27 │ 21.123 │ │ 2001-12-28 │ 21.266 │ -│ 2001-12-31 │ 21.417 │

As mentioned previously, we lose the first nine observations to the consuming nature of this operation. They are not missing per se, they simply do not exist.

TimeSeries.moving — Function
moving(f, ta::TimeArray{T,1}, w::Integer; padding = false)

Apply user-defined function f to a 1D TimeArray with window size w.

Example

To calculate the simple moving average of a time series:

moving(mean, ta, 10)
source
moving(f, ta::TimeArray{T,2}, w::Integer; padding = false, dims = 1, colnames = [...])

Example

In case of dims = 2, the user-defined function f will get a 2D Array as input.

moving(ohlc, 10, dims = 2, colnames = [:A, ...]) do
+│ 2001-12-31 │ 21.417  │

As mentioned previously, we lose the first nine observations to the consuming nature of this operation. They are not missing per se, they simply do not exist.

TimeSeries.moving — Function
moving(f, ta::TimeArray{T,1}, w::Integer; padding = false)

Apply user-defined function f to a 1D TimeArray with window size w.

Example

To calculate the simple moving average of a time series:

moving(mean, ta, 10)
source
moving(f, ta::TimeArray{T,2}, w::Integer; padding = false, dims = 1, colnames = [...])

Example

In case of dims = 2, the user-defined function f will get a 2D Array as input.

moving(ohlc, 10, dims = 2, colnames = [:A, ...]) do
     # given that `ohlc` is a 500x4 `TimeArray`,
     # size(A) is (10, 4)
     ...
-end
source

upto

Another operation common in time series analysis is an aggregation function. TimeSeries supports this with the upto method. Suppose you want to keep track of the sum of all the values from the beginning to the present timestamp. You would use the upto method like this:

julia> using TimeSeries
+end
source

upto

Another operation common in time series analysis is an aggregation function. TimeSeries supports this with the upto method. Suppose you want to keep track of the sum of all the values from the beginning to the present timestamp. You would use the upto method like this:

julia> using TimeSeries
 
 julia> using MarketData
 
@@ -172,4 +172,4 @@
 │ 2001-12-26 │ 23028.84 │
 │ 2001-12-27 │ 23050.91 │
 │ 2001-12-28 │ 23073.34 │
-│ 2001-12-31 │ 23095.24 │
+│ 2001-12-31 │ 23095.24 │ diff --git a/dev/bw.svg b/dev/bw.svg index 36dedfff..9858a5e8 100644 --- a/dev/bw.svg +++ b/dev/bw.svg @@ -1,384 +1,354 @@ - + - - + - - + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + diff --git a/dev/combine/index.html b/dev/combine/index.html index 63cca054..8b74ee78 100644 --- a/dev/combine/index.html +++ b/dev/combine/index.html @@ -38,7 +38,7 @@ 47 julia> meta(merge(AppleCat, CatApple))
Base.merge — Function
merge(ta1::TimeArray{T}, ta2::TimeArray{T}, [tas::TimeArray{T}...];
-      method = :inner, colnames = [...], padvalue = NaN)

Merge several TimeArrays along with the time index.

Argument

  • method::Symbol: :inner, :outer, :left or :right.
source

collapse

The collapse method allows for compressing data into a larger time frame. For example, converting daily data into monthly data. When compressing dates, something rational has to be done with the values that lived in the more granular time frame. To define what happens, a function call is made. In our example, we want to compress the daily cl closing prices from daily to monthly. It makes sense for us to take the last value known and have that represented with the corresponding timestamp. A non-exhaustive list of valid time methods is presented below.

Dates methodTime length
Dates.quarterquarterly
daydaily
weekweekly, starting from Monday.
monthmonthly
yearyearly
hourhourly
minuteminutely
secondsecondly

Showing this code in REPL:

julia> using TimeSeries
+      method = :inner, colnames = [...], padvalue = NaN)

Merge several TimeArrays along with the time index.

Argument

source

collapse

The collapse method allows for compressing data into a larger time frame. For example, converting daily data into monthly data. When compressing dates, something rational has to be done with the values that lived in the more granular time frame. To define what happens, a function call is made. In our example, we want to compress the daily cl closing prices from daily to monthly. It makes sense for us to take the last value known and have that represented with the corresponding timestamp. A non-exhaustive list of valid time methods is presented below.

Dates methodTime length
Dates.quarterquarterly
daydaily
weekweekly, starting from Monday.
monthmonthly
yearyearly
hourhourly
minuteminutely
secondsecondly

Showing this code in REPL:

julia> using TimeSeries
 
 julia> using MarketData
 
@@ -95,7 +95,7 @@
 │ 2015-10-02 │ 2     │
 │ 2015-10-02 │ 4     │
 │ 2015-10-03 │ 3     │
-│ 2015-10-03 │ 5     │
source

map

This function allows complete transformation of the data within the time series, with alteration on both the time stamps and the associated values. It works exactly like Base.map: the first argument is a binary function (the time stamp and the values) that returns two values, respectively the new time stamp and the new vector of values. It does not perform any kind of compression like collapse, but rather transformations.

The simplest example is to postpone all time stamps in the given time series, here by one year:

julia> using TimeSeries
+│ 2015-10-03 │ 5     │
source

map

This function allows complete transformation of the data within the time series, with alteration on both the time stamps and the associated values. It works exactly like Base.map: the first argument is a binary function (the time stamp and the values) that returns two values, respectively the new time stamp and the new vector of values. It does not perform any kind of compression like collapse, but rather transformations.

The simplest example is to postpone all time stamps in the given time series, here by one year:

julia> using TimeSeries
 
 julia> using Dates
 
@@ -111,4 +111,4 @@
 │            │ A     │
 ├────────────┼───────┤
 │ 2016-10-01 │ 15    │
-│ 2016-11-01 │ 16    │
+│ 2016-11-01 │ 16 │ diff --git a/dev/cs.svg b/dev/cs.svg index 47c566af..21e27f91 100644 --- a/dev/cs.svg +++ b/dev/cs.svg @@ -1,384 +1,354 @@ - + - - + - - + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + diff --git a/dev/dotfile/index.html b/dev/dotfile/index.html index e5cda1e4..f8fadc19 100644 --- a/dev/dotfile/index.html +++ b/dev/dotfile/index.html @@ -114,4 +114,4 @@ │ 2001-12-26 │ 21.36 │ │ 2001-12-27 │ 21.49 │ │ 2001-12-28 │ 22.07 │ -│ 2001-12-31 │ 22.43 │

Other const values include DOTCIRCLE and QUESTION. The UNICORN value is a feature request.

+│ 2001-12-31 │ 22.43 │

Other const values include DOTCIRCLE and QUESTION. The UNICORN value is a feature request.

diff --git a/dev/getting_started/index.html b/dev/getting_started/index.html index 23edf1e8..a070fb65 100644 --- a/dev/getting_started/index.html +++ b/dev/getting_started/index.html @@ -8,19 +8,19 @@ 365×1 TimeArray{Float64,1,Date,Array{Float64,1}} 2018-01-01 to 2018-12-31 │ │ A │ ├────────────┼────────┤ -│ 2018-01-01 │ 0.78 │ -│ 2018-01-02 │ 0.7668 │ -│ 2018-01-03 │ 0.2908 │ -│ 2018-01-04 │ 0.4065 │ -│ 2018-01-05 │ 0.3666 │ -│ 2018-01-06 │ 0.1149 │ -│ 2018-01-07 │ 0.1253 │ -│ 2018-01-08 │ 0.257 │ +│ 2018-01-01 │ 0.9147 │ +│ 2018-01-02 │ 0.9695 │ +│ 2018-01-03 │ 0.9249 │ +│ 2018-01-04 │ 0.0016 │ +│ 2018-01-05 │ 0.6146 │ +│ 2018-01-06 │ 0.326 │ +│ 2018-01-07 │ 0.3341 │ +│ 2018-01-08 │ 0.2197 │ │ ⋮ │ ⋮ │ -│ 2018-12-25 │ 0.8381 │ -│ 2018-12-26 │ 0.6109 │ -│ 2018-12-27 │ 0.4536 │ -│ 2018-12-28 │ 0.3411 │ -│ 2018-12-29 │ 0.6153 │ -│ 2018-12-30 │ 0.3045 │ -│ 2018-12-31 │ 0.2874 │ +│ 2018-12-25 │ 0.0804 │ +│ 2018-12-26 │ 0.8145 │ +│ 2018-12-27 │ 0.6865 │ +│ 2018-12-28 │ 0.988 │ +│ 2018-12-29 │ 0.2997 │ +│ 2018-12-30 │ 0.4598 │ +│ 2018-12-31 │ 0.6629 │ diff --git a/dev/index.html b/dev/index.html index 48e0d734..ccca0e8b 100644 --- a/dev/index.html +++ b/dev/index.html @@ -1,2 +1,2 @@ -TimeSeries Overview · TimeSeries.jl
Edit on GitHub

TimeSeries Overview

The TimeSeries package provides convenient methods for working with time series data in Julia.

Contents

+TimeSeries Overview · TimeSeries.jl
Edit on GitHub

TimeSeries Overview

The TimeSeries package provides convenient methods for working with time series data in Julia.

Contents

diff --git a/dev/indexing/index.html b/dev/indexing/index.html index ecb01b48..0dd82330 100644 --- a/dev/indexing/index.html +++ b/dev/indexing/index.html @@ -139,4 +139,4 @@ 1×1 TimeArray{Float64,1,Date,Array{Float64,1}} 2000-01-03 to 2000-01-03 │ │ Open │ ├────────────┼────────┤ -│ 2000-01-03 │ 104.88 │ +│ 2000-01-03 │ 104.88 │ diff --git a/dev/modify/index.html b/dev/modify/index.html index 811f9b50..a4fffc62 100644 --- a/dev/modify/index.html +++ b/dev/modify/index.html @@ -48,7 +48,7 @@ │ 2000-01-03 │ 104.88 │ 112.5 │ 101.69 │ 111.94 │
TimeSeries.rename — Function
rename(ta::TimeArray, colnames::Vector{Symbol})
 rename(ta::TimeArray, colname::Symbol)
 rename(ta::TimeArray, orig => new, ...)
-rename(f::Base.Callable, ta, colnametyp)

Rename the columns of a TimeArray.

See also rename!.

Arguments

  • colnametyp is the input type for the function f. The valid value is Symbol or String.
source
TimeSeries.rename! — Function
rename!(ta::TimeArray, colnames::Vector{Symbol})
+rename(f::Base.Callable, ta, colnametyp)

Rename the columns of a TimeArray.

See also rename!.

Arguments

  • colnametyp is the input type for the function f. The valid value is Symbol or String.
source
TimeSeries.rename! — Function
rename!(ta::TimeArray, colnames::Vector{Symbol})
 rename!(ta::TimeArray, colname::Symbol)
 rename!(ta::TimeArray, orig => new, ...)
-rename!(f::Base.Callable, ta, colnametyp)

In-place rename the columns of a TimeArray.

See also rename.

Arguments

  • colnametyp is the input type for the function f. The valid value is Symbol or String.
source
+rename!(f::Base.Callable, ta, colnametyp)

In-place rename the columns of a TimeArray.

See also rename.

Arguments

source diff --git a/dev/multi-series.svg b/dev/multi-series.svg index 1b5ca133..c9d8eba4 100644 --- a/dev/multi-series.svg +++ b/dev/multi-series.svg @@ -1,116 +1,116 @@ - + - - + - - + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + diff --git a/dev/operators/index.html b/dev/operators/index.html index 2ba532e1..0d242e39 100644 --- a/dev/operators/index.html +++ b/dev/operators/index.html @@ -1,2 +1,2 @@ -Mathematical, comparison, and logical operators · TimeSeries.jl
Edit on GitHub

Mathematical, comparison, and logical operators

TimeSeries supports common mathematical (such as .+), comparison (such as .==) , and logic (such as .&) operators. The operations are only calculated on values that share a timestamp. All of the operations must be treat as dot-call.

Mathematical

Mathematical operators create a TimeArray object where values are computed on shared timestamps when two TimeArray objects are provided. Operations between a single TimeArray and Int or Float are also supported. The number can precede the TimeArray object or vice versa (e.g. cl .+ 2 or 2 .+ cl). Broadcasting single-column arrays over multiple columns to perform operations is also supported.

The exclusion of / and ^ from this logic are special cases. In matrix operations / has been confused with being equivalent to the inverse, and because of the confusion base has excluded it. It is likewise excluded here. Base uses ^ to indicate matrix self-multiplication, and so it is not implemented in this context.

OperatorDescription
.+arithmetic element-wise addition
.-arithmetic element-wise subtraction
.*arithmetic element-wise multiplication
./arithmetic element-wise division
.^arithmetic element-wise exponentiation
.%arithmetic element-wise remainder

Comparison

Comparison operators create a TimeArray of type Bool. Values are compared on shared timestamps when two TimeArray objects are provided. Broadcasting single-column arrays over multiple columns to perform comparisons is supported, as are comparisons between a single TimeArray and Int, Float, or Bool values. The semantics of an non-dot operators (>) is unclear, and such operators are not supported.

OperatorDescription
.>element-wise greater-than comparison
.<element-wise less-than comparison
.==element-wise equivalent comparison
.>=element-wise greater-than or equal comparison
.<=element-wise less-than or equal comparison
.!=element-wise not-equivalent comparison

Logic

Logical operators are defined for TimeArrays of type Bool and return a TimeArray of type Bool. Values are computed on shared timestamps when two TimeArray objects are provided. Operations between a single TimeArray and Bool are also supported.

OperatorDescription
.&element-wise logical AND
.|element-wise logical OR
.!, .~element-wise logical NOT
.⊻element-wise logical XOR
+Mathematical, comparison, and logical operators · TimeSeries.jl
Edit on GitHub

Mathematical, comparison, and logical operators

TimeSeries supports common mathematical (such as .+), comparison (such as .==) , and logic (such as .&) operators. The operations are only calculated on values that share a timestamp. All of the operations must be treat as dot-call.

Mathematical

Mathematical operators create a TimeArray object where values are computed on shared timestamps when two TimeArray objects are provided. Operations between a single TimeArray and Int or Float are also supported. The number can precede the TimeArray object or vice versa (e.g. cl .+ 2 or 2 .+ cl). Broadcasting single-column arrays over multiple columns to perform operations is also supported.

The exclusion of / and ^ from this logic are special cases. In matrix operations / has been confused with being equivalent to the inverse, and because of the confusion base has excluded it. It is likewise excluded here. Base uses ^ to indicate matrix self-multiplication, and so it is not implemented in this context.

OperatorDescription
.+arithmetic element-wise addition
.-arithmetic element-wise subtraction
.*arithmetic element-wise multiplication
./arithmetic element-wise division
.^arithmetic element-wise exponentiation
.%arithmetic element-wise remainder

Comparison

Comparison operators create a TimeArray of type Bool. Values are compared on shared timestamps when two TimeArray objects are provided. Broadcasting single-column arrays over multiple columns to perform comparisons is supported, as are comparisons between a single TimeArray and Int, Float, or Bool values. The semantics of an non-dot operators (>) is unclear, and such operators are not supported.

OperatorDescription
.>element-wise greater-than comparison
.<element-wise less-than comparison
.==element-wise equivalent comparison
.>=element-wise greater-than or equal comparison
.<=element-wise less-than or equal comparison
.!=element-wise not-equivalent comparison

Logic

Logical operators are defined for TimeArrays of type Bool and return a TimeArray of type Bool. Values are computed on shared timestamps when two TimeArray objects are provided. Operations between a single TimeArray and Bool are also supported.

OperatorDescription
.&element-wise logical AND
.|element-wise logical OR
.!, .~element-wise logical NOT
.⊻element-wise logical XOR
diff --git a/dev/plotting/index.html b/dev/plotting/index.html index 0e785c77..54abb3c9 100644 --- a/dev/plotting/index.html +++ b/dev/plotting/index.html @@ -1,22 +1,22 @@ Plotting · TimeSeries.jl
Edit on GitHub

Plotting

TimeSeries defines a recipe that allows plotting to a number of different plotting packages using the Plots.jl framework (no plotting packages will be automatically installed by TimeSeries).

Here we use the data from Yahoo Fiance as a demo.

using Plots, MarketData, TimeSeries
 gr()
-ta = yahoo(:GOOG, YahooOpt(period1 = now() - Month(1)))
22×6 TimeArray{Float64,2,Date,Array{Float64,2}} 2023-04-17 to 2023-05-16
-│            │ Open    │ High    │ Low     │ Close  │ AdjClose │ Volume      │
-├────────────┼─────────┼─────────┼─────────┼────────┼──────────┼─────────────┤
-│ 2023-04-17 │ 105.43  │ 106.71  │ 105.32  │ 106.42 │ 106.42   │ 2.90434e7   │
-│ 2023-04-18 │ 107.0   │ 107.05  │ 104.78  │ 105.12 │ 105.12   │ 1.76414e7   │
-│ 2023-04-19 │ 104.215 │ 105.725 │ 103.8   │ 105.02 │ 105.02   │ 1.6732e7    │
-│ 2023-04-20 │ 104.65  │ 106.888 │ 104.64  │ 105.9  │ 105.9    │ 2.25153e7   │
-│ 2023-04-21 │ 106.09  │ 106.64  │ 105.485 │ 105.91 │ 105.91   │ 2.2379e7    │
-│ 2023-04-24 │ 106.05  │ 107.32  │ 105.36  │ 106.78 │ 106.78   │ 2.14109e7   │
-│ 2023-04-25 │ 106.61  │ 107.44  │ 104.56  │ 104.61 │ 104.61   │ 3.14081e7   │
-│ 2023-04-26 │ 105.56  │ 107.02  │ 103.27  │ 104.45 │ 104.45   │ 3.70682e7   │
-│ ⋮          │ ⋮       │ ⋮       │ ⋮       │ ⋮      │ ⋮        │ ⋮           │
-│ 2023-05-08 │ 105.795 │ 108.42  │ 105.79  │ 108.24 │ 108.24   │ 1.7266e7    │
-│ 2023-05-09 │ 108.78  │ 110.595 │ 107.725 │ 107.94 │ 107.94   │ 2.47824e7   │
-│ 2023-05-10 │ 108.55  │ 113.51  │ 108.48  │ 112.28 │ 112.28   │ 4.75335e7   │
-│ 2023-05-11 │ 115.86  │ 118.44  │ 114.93  │ 116.9  │ 116.9    │ 5.71151e7   │
-│ 2023-05-12 │ 117.0   │ 118.26  │ 116.55  │ 117.92 │ 117.92   │ 3.12725e7   │
-│ 2023-05-15 │ 116.49  │ 118.795 │ 116.48  │ 116.96 │ 116.96   │ 2.21079e7   │
-│ 2023-05-16 │ 116.83  │ 121.2   │ 116.84  │ 120.09 │ 120.09   │ 3.1756724e7 │

Plotting as multiple series

The recipe allows TimeArray objects to be passed as input to plot. The recipe will plot each variable as an individual line, aligning all variables to the same y axis. backend).

plot(ta[:Open, :High, :Low, :Close])

Plotting candlestick

We have seriestype = :candlestick support that requires four columns exist in the input. They are open, high, low and close (case-insensitive).

plot(ta, seriestype = :candlestick)

Other available attributes

  • bar_width::Float64 the valid value is from 0 to 1.
plot(ta, seriestype = :candlestick, bar_width = 0.7)

  • xticks::Int for controlling the density of x axis labels.
plot(ta, seriestype = :candlestick, xticks = 3, xrotation = 60)

+ta = yahoo(:GOOG, YahooOpt(period1 = now() - Month(1)))
20×6 TimeArray{Float64,2,Date,Array{Float64,2}} 2023-10-02 to 2023-10-27
+│            │ Open    │ High    │ Low     │ Close  │ AdjClose │ Volume    │
+├────────────┼─────────┼─────────┼─────────┼────────┼──────────┼───────────┤
+│ 2023-10-02 │ 132.155 │ 135.36  │ 132.065 │ 135.17 │ 135.17   │ 1.92104e7 │
+│ 2023-10-03 │ 134.93  │ 135.24  │ 132.815 │ 133.3  │ 133.3    │ 1.96287e7 │
+│ 2023-10-04 │ 133.66  │ 136.57  │ 133.43  │ 136.27 │ 136.27   │ 2.2848e7  │
+│ 2023-10-05 │ 136.13  │ 136.5   │ 134.455 │ 135.99 │ 135.99   │ 1.59229e7 │
+│ 2023-10-06 │ 134.94  │ 139.186 │ 134.94  │ 138.73 │ 138.73   │ 2.08193e7 │
+│ 2023-10-09 │ 137.99  │ 139.97  │ 136.7   │ 139.5  │ 139.5    │ 1.65991e7 │
+│ 2023-10-10 │ 139.51  │ 140.74  │ 138.43  │ 139.2  │ 139.2    │ 1.95549e7 │
+│ 2023-10-11 │ 139.85  │ 142.22  │ 139.84  │ 141.7  │ 141.7    │ 2.01463e7 │
+│ ⋮          │ ⋮       │ ⋮       │ ⋮       │ ⋮      │ ⋮        │ ⋮         │
+│ 2023-10-19 │ 139.8   │ 141.005 │ 138.6   │ 138.98 │ 138.98   │ 2.18312e7 │
+│ 2023-10-20 │ 138.59  │ 139.04  │ 136.245 │ 136.74 │ 136.74   │ 2.49539e7 │
+│ 2023-10-23 │ 136.23  │ 139.02  │ 135.11  │ 137.9  │ 137.9    │ 2.07807e7 │
+│ 2023-10-24 │ 139.16  │ 140.71  │ 138.75  │ 140.12 │ 140.12   │ 2.65352e7 │
+│ 2023-10-25 │ 129.77  │ 130.1   │ 126.09  │ 126.67 │ 126.67   │ 5.87961e7 │
+│ 2023-10-26 │ 124.47  │ 125.46  │ 122.32  │ 123.44 │ 123.44   │ 3.39074e7 │
+│ 2023-10-27 │ 124.03  │ 124.44  │ 121.46  │ 123.4  │ 123.4    │ 3.7349e7  │

Plotting as multiple series

The recipe allows TimeArray objects to be passed as input to plot. The recipe will plot each variable as an individual line, aligning all variables to the same y axis. backend).

plot(ta[:Open, :High, :Low, :Close])

Plotting candlestick

We have seriestype = :candlestick support that requires four columns exist in the input. They are open, high, low and close (case-insensitive).

plot(ta, seriestype = :candlestick)

Other available attributes

  • bar_width::Float64 the valid value is from 0 to 1.
plot(ta, seriestype = :candlestick, bar_width = 0.7)

  • xticks::Int for controlling the density of x axis labels.
plot(ta, seriestype = :candlestick, xticks = 3, xrotation = 60)

diff --git a/dev/readwrite/index.html b/dev/readwrite/index.html index 5046c805..f9e9f222 100644 --- a/dev/readwrite/index.html +++ b/dev/readwrite/index.html @@ -7,4 +7,4 @@ 2000-01-04,102.5 2000-01-05,104.0 2000-01-06,95.0 -2000-01-07,99.5 +2000-01-07,99.5 diff --git a/dev/search/index.html b/dev/search/index.html index 07e18d19..d8fccb18 100644 --- a/dev/search/index.html +++ b/dev/search/index.html @@ -1,2 +1,2 @@ -Search · TimeSeries.jl +Search · TimeSeries.jl diff --git a/dev/split/index.html b/dev/split/index.html index dc9a8b74..91dd3f15 100644 --- a/dev/split/index.html +++ b/dev/split/index.html @@ -174,4 +174,4 @@ ├────────────┼───────┤ │ 2001-12-27 │ 22.07 │ │ 2001-12-28 │ 22.43 │ -│ 2001-12-31 │ 21.9 │ +│ 2001-12-31 │ 21.9 │ diff --git a/dev/tables/index.html b/dev/tables/index.html index 17e618ad..f5def360 100644 --- a/dev/tables/index.html +++ b/dev/tables/index.html @@ -58,4 +58,4 @@ │ 2001-12-28 │ 21.97 │ 23.0 │ 21.96 │ 22.43 │ │ 2001-12-31 │ 22.51 │ 22.66 │ 21.83 │ 21.9 │

Save a TimeArray via CSV.jl

using CSV
 CSV.write(filename, ta)

Load a TimeArray from csv file via CSV.jl

using CSV
-TimeArray(CSV.File(filename), timestamp = :timestamp)
+TimeArray(CSV.File(filename), timestamp = :timestamp) diff --git a/dev/timearray/index.html b/dev/timearray/index.html index e9335ad7..65071ef4 100644 --- a/dev/timearray/index.html +++ b/dev/timearray/index.html @@ -13,9 +13,9 @@ col1 = [10.2, 11.2], col2 = [20.2, 21.2], col3 = [30.2, 31.2]) -ta = TimeArray(data; timestamp = :datetime, meta = "Example")source

Fields getter functions

There are four field getter functions exported. They are named as same as the field names.

Base.values — Function
values(ta::TimeArray)

Get the underlying value table of a TimeArray.

source
TimeSeries.colnames — Function
colnames(ta::TimeArray)

Get the column names of a TimeArray.

Examples

julia> colnames(ohlc)
+ta = TimeArray(data; timestamp = :datetime, meta = "Example")
source

Fields getter functions

There are four field getter functions exported. They are named as same as the field names.

Base.values — Function
values(ta::TimeArray)

Get the underlying value table of a TimeArray.

source
TimeSeries.colnames — Function
colnames(ta::TimeArray)

Get the column names of a TimeArray.

Examples

julia> colnames(ohlc)
 4-element Array{Symbol,1}:
  :Open
  :High
  :Low
- :Close
source
+ :Closesource diff --git a/dev/xticks.svg b/dev/xticks.svg index a18f2241..5c23ad06 100644 --- a/dev/xticks.svg +++ b/dev/xticks.svg @@ -1,384 +1,354 @@ - + - - + - - + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + - + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + +