MATLAB® > Financial Charts > Time Series and Date Axes
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Time Series and Date Axes in MATLAB®

How to make Time Series plots in MATLAB® with Plotly.


Plot Timetable Variables

Read data from a spreadsheet to a table. Then convert the table to a timetable. The first variable that contains dates and times, OutageTime, provides the row times for the timetable. Display the first five rows.

tbl = readtable('outages.csv');
tbl = table2timetable(tbl);
head(tbl,5)

ans =

  5x5 timetable

       OutageTime          Region           Loss         Customers     RestorationTime            Cause       
    ________________    _____________    ___________    ___________    ________________    ___________________

    2002-02-01 12:18    {'SouthWest'}    458.9772218    1820159.482    2002-02-07 16:50    {'winter storm'   }
    2003-01-23 00:49    {'SouthEast'}    530.1399497    212035.3001                 NaT    {'winter storm'   }
    2003-02-07 21:15    {'SouthEast'}    289.4035493    142938.6282    2003-02-17 08:14    {'winter storm'   }
    2004-04-06 05:44    {'West'     }    434.8053524    340371.0338    2004-04-06 06:10    {'equipment fault'}
    2002-03-16 06:18    {'MidWest'  }    186.4367788     212754.055    2002-03-18 23:23    {'severe storm'   }

Sort the timetable so that its row times are in order. The row times of a timetable do not need to be in order. However, if you use the row times as the x-axis of a plot, then it is better to ensure the timetable is sorted by its row times.

tbl = readtable('outages.csv');
tbl = table2timetable(tbl);

tbl = sortrows(tbl);
head(tbl,5)

ans =

  5x5 timetable

       OutageTime          Region           Loss         Customers     RestorationTime          Cause      
    ________________    _____________    ___________    ___________    ________________    ________________

    2002-02-01 12:18    {'SouthWest'}    458.9772218    1820159.482    2002-02-07 16:50    {'winter storm'}
    2002-03-05 17:53    {'MidWest'  }    96.56294147    286657.9948    2002-03-10 14:41    {'wind'        }
    2002-03-16 06:18    {'MidWest'  }    186.4367788     212754.055    2002-03-18 23:23    {'severe storm'}
    2002-03-26 01:59    {'MidWest'  }    388.0408135    564223.7059    2002-03-28 19:55    {'winter storm'}
    2002-04-20 16:46    {'MidWest'  }    23141.16309            NaN                 NaT    {'unknown'     }

Create a stacked plot of data from tbl. The row times, OutageTime, provide the values along the x-axis. The stackedplot function plots the values from the Loss, Customers, and RestorationTime variables, with each variable plotted along its own y-axis. However, the plot does not include the Region and Cause variables because they contain data that cannot be plotted.

tbl = readtable('outages.csv');
tbl = table2timetable(tbl);

tbl = sortrows(tbl);

stackedplot(tbl)

fig2plotly(gcf);

Specify Variables

Create a table from patient data. Display the first three rows.

tbl = readtable('patients.xls');
head(tbl,3)

ans =

  3x10 table

      LastName        Gender      Age              Location               Height    Weight    Smoker    Systolic    Diastolic    SelfAssessedHealthStatus
    ____________    __________    ___    _____________________________    ______    ______    ______    ________    _________    ________________________

    {'Smith'   }    {'Male'  }    38     {'County General Hospital'  }      71       176      true        124          93             {'Excellent'}      
    {'Johnson' }    {'Male'  }    43     {'VA Hospital'              }      69       163      false       109          77             {'Fair'     }      
    {'Williams'}    {'Female'}    38     {'St. Mary's Medical Center'}      64       131      false       125          83             {'Good'     }

Plot only four of the variables from the table.

tbl = readtable('patients.xls');

stackedplot(tbl,{'Height','Weight','Systolic','Diastolic'})

fig2plotly(gcf);

Reorder Variables

Create a timetable and display its first three rows.

tbl = readtable('outages.csv');
tbl = table2timetable(tbl);
tbl = sortrows(tbl);
head(tbl,3)

ans =

  3x5 timetable

       OutageTime          Region           Loss         Customers     RestorationTime          Cause      
    ________________    _____________    ___________    ___________    ________________    ________________

    2002-02-01 12:18    {'SouthWest'}    458.9772218    1820159.482    2002-02-07 16:50    {'winter storm'}
    2002-03-05 17:53    {'MidWest'  }    96.56294147    286657.9948    2002-03-10 14:41    {'wind'        }
    2002-03-16 06:18    {'MidWest'  }    186.4367788     212754.055    2002-03-18 23:23    {'severe storm'}

Reorder the variables by specifying them in an order that differs from their order in the table. For example, RestorationTime is the last variable in the timetable that can be plotted. By default, stackedplot places it at the bottom of the plot. But you can reorder the variables to put RestorationTime at the top.

tbl = readtable('outages.csv');
tbl = table2timetable(tbl);
tbl = sortrows(tbl);

stackedplot(tbl,{'RestorationTime','Loss','Customers'})

fig2plotly(gcf);

There are also other ways to reorder the variables.

  • Specify them by their numeric order in the table: stackedplot(tbl,[4 2 3]);
  • Return a StackedLineChart object and reorder the values in its DisplayVariables property: s = stackedplot(tbl); s.DisplayVariables = {'RestorationTime','Loss','Customers'}

Plot Multiple Variables Using One Y-Axis

Create a table from a subset of patient data, using the Weight, Systolic, and Diastolic variables.

load patients
tbl = table(Weight,Systolic,Diastolic);
head(tbl,3)

ans =

  3x3 table

    Weight    Systolic    Diastolic
    ______    ________    _________

     176        124          93    
     163        109          77    
     131        125          83

Create a stacked plot, with Systolic and Diastolic plotted using the same y-axis. To plot variables together, specify them within a nested cell array.

load patients
tbl = table(Weight,Systolic,Diastolic);

vars = [{'Systolic','Diastolic'},'Weight'];

load patients
tbl = table(Weight,Systolic,Diastolic);

vars = [{'Systolic','Diastolic'},'Weight'];

stackedplot(tbl,vars);

fig2plotly(gcf);

Plot Columns of Matrix

Create a numeric matrix and a numeric vector.

Create a stacked plot using X and Y.

X = [0:4:20]

Y = randi(100,6,3)

stackedplot(X,Y)

fig2plotly(gcf);

X =

     0     4     8    12    16    20


Y =

    19    42    34
     5    99    67
    11    95    25
    62    68    30
    94    99    69
    36    77    53

Specify Title and Labels Using Name-Value Pairs

Load a timetable that has a set of weather measurements. Display its first three rows.

load outdoors
outdoors(1:3,:);

Create a stacked plot. Specify the title and labels for the y-axes using name-value pair arguments. You can use name-values pairs to change any properties from their defaults values. (Also note that you can specify the degree symbol using char(176).)

load outdoors
outdoors(1:3,:);

degreeSymbol = char(176);
newYlabels = {'RH (%)',['T (' degreeSymbol 'F)'],'P (in Hg)'};
stackedplot(outdoors,'Title','Weather Data','DisplayLabels',newYlabels);

fig2plotly(gcf);

Change Individual Plots to Scatter and Stair Plots

The stackedplot function returns a StackedLineChart object. You can use it to set the same property value for all plots, or to set different property values for individual plots. In this example, first change the line widths for all plots in a stacked plot. Then, use the PlotType property of individual plots, so that the stacked plot has a line plot, scatter plot, and stair plot.

Load a timetable that has a set of weather measurements. 

load outdoors
outdoors(1:3,:);

Create a stacked plot and return a StackedLineChart object.

load outdoors
outdoors(1:3,:);

s = stackedplot(outdoors);

fig2plotly(gcf);

The object provides access to many properties that apply to all of the plots. For example, you can use s.LineWidth to make the lines wider.

load outdoors
outdoors(1:3,:);

s = stackedplot(outdoors);

s.LineWidth = 2;

fig2plotly(gcf);

The object also provides access to arrays of objects that you can use to modify the lines and y-axes for individual plots. To access properties of individual lines, use s.LineProperties. For each plot, you can specify a different line style, marker, plot type, and so on.

load outdoors
outdoors(1:3,:);

s = stackedplot(outdoors);

s.LineWidth = 2;

s.LineProperties

ans = 

  3x1 StackedLineProperties array with properties:

    Color
    MarkerFaceColor
    MarkerEdgeColor
    LineStyle
    LineWidth
    Marker
    MarkerSize
    PlotType

Change the second plot to a scatter plot, and the third plot to a stair plot, using the PlotType property.

load outdoors
outdoors(1:3,:);

s = stackedplot(outdoors);

s.LineWidth = 2;

s.LineProperties(2).PlotType = 'scatter';
s.LineProperties(3).PlotType = 'stairs';

fig2plotly(gcf);

You also can access individual y-axes through the s.AxesProperties property.

load outdoors
outdoors(1:3,:);

s = stackedplot(outdoors);

s.LineWidth = 2;

s.LineProperties(2).PlotType = 'scatter';
s.LineProperties(3).PlotType = 'stairs';

s.AxesProperties

ans = 

  3x1 StackedAxesProperties array with properties:

    YLimits
    YScale
    LegendLabels
    LegendLocation
    LegendVisible

Date Strings

data = {...
  struct(...
    'x', { {'2013-10-04 22:23:00', '2013-11-04 22:23:00', '2013-12-04 22:23:00'} }, ...
    'y', [1, 3, 6], ...
    'type', 'scatter')...
};

plotly(data);