I use prawn (1.0.0) and managed to got a table inside a table. Everything good so far.
But the font size in the inner table is different (i guess the default font size) than the outside table.
pdf = Prawn::Document.new
table_data = []
table_data << ['iDirect', representation.idirect.yesno]
people = []
representation.people.each do |person|
person_fullname = "#{person.lastname} #{person.firstname}"
person_fullname_title = if person.title.empty?
person_fullname
else
"#{person_fullname}, #{person.title}"
end
people << [person.function, person_fullname_title]
end
table_data << ['Personen', people]
pdf.table table_data, cell_style: { size: 7, borders: [:bottom] }, column_widths: [90, 430]
I tried to override the default font size by using a constructor like
# this doesn't affect the font size in the inside table
pdf = Prawn::Document.new(:page_size => 'A4', :page_layout => :portrait, :size => 7)
How can i change the font size of the inside table?
You could also add inside your if else on the cells, something like
"#{person_fullname, :size => 7}, #{person.title, :size => 7}"
I could solve this with a simple
pdf.font_size 7
Related
I have a FeatureCollection with a column named Dominance which has classified regions into stakeholder dominance. In this case, Dominance contains values as strings; specifically 'Small', 'Medium', 'Large' and 'Others'.
I want to replace these values/strings with 1,2,3 and 4. For that, I use the codes below:
var Shape = ee.FeatureCollection('XYZ')
var Shape_custom = Shape.select(['Dominance'])
var conditional = function(feat) {
return ee.Algorithms.If(feat.get('Dominance').eq('Small'),
feat.set({class: 1}),
feat)
}
var test = Shape_custom.map(conditional)
## This I plan to repeat for all classes
However, I am not able to change the values. The error I am getting is feat.get(...).eq is not a function.
What am I doing wrong here?
The simplest way to do this kind of mapping is using a dictionary. That way you do not need more code for each additional case.
var mapping = ee.Dictionary({
'Small': 1,
'Medium': 2,
'Large': 3,
'Others': 4
});
var mapped = Shape
.select(['Dominance'])
.map(function (feature) {
return feature.set('class', mapping.get(feature.get('Dominance')));
});
https://code.earthengine.google.com/8c58d9d24e6bfeca04e2a92b76d623a2
I´ve been struggling with this:
My table shows 3 records but when expanding there are like 100 columns. I used this code:
#"Expanded Data" = Table.ExpandTableColumn(#"Source", "Document", List.Union(List.Transform(#"Source"[Document]), each Table.ColumnNames(_))),
but it's not working. How can I expand simultaneously all columns? Also, inside those columns there are even more, for example I expand the first time end then those new columns have more records inside.
What could I do? Thanks in advance!
Try this ExpandAllRecords function - it recursively expands every Record-type column:
https://gist.github.com/Mike-Honey/0a252edf66c3c486b69b
This should work for Records Columns.
let
ExpandIt = (TableToExpand as table, optional ColumnName as text) =>
let
ListAllColumns = Table.ColumnNames(TableToExpand),
ColumnsTotal = Table.ColumnCount(TableToExpand),
CurrentColumnIndex = if (ColumnName = null) then 0 else List.PositionOf(ListAllColumns, ColumnName),
CurrentColumnName = ListAllColumns{CurrentColumnIndex},
CurrentColumnContent = Table.Column(TableToExpand, CurrentColumnName),
IsExpandable = if List.IsEmpty(List.Distinct(List.Select(CurrentColumnContent, each _ is record))) then false else true,
FieldsToExpand = if IsExpandable then Record.FieldNames(List.First(List.Select(CurrentColumnContent, each _ is record))) else {},
ColumnNewNames = List.Transform(FieldsToExpand, each CurrentColumnName &"."& _),
ExpandedTable = if IsExpandable then Table.ExpandRecordColumn(TableToExpand, CurrentColumnName, FieldsToExpand, ColumnNewNames) else TableToExpand,
NextColumnIndex = CurrentColumnIndex+1,
NextColumnName = ListAllColumns{NextColumnIndex},
OutputTable = if NextColumnIndex > ColumnsTotal-1 then ExpandedTable else #fx_ExpandIt(ExpandedTable, NextColumnName)
in
OutputTable
in
ExpandIt
This basically takes Table to Transform as the main argument,and then one by one checks if the Column Record is expandable (if column has "records" in it, it will expand it, otherwise move to next column and checks it again).
Then it returns the Output table once everything is expanded.
This function is calling the function from inside for each iteration.
I am trying to create a reusable function in Power Query that will be used by several tables.
This works well (written in blank query):
let
is_emergency = (color as text) =>
if color = "red" or color = "orange" then
"emergency"
else
"not emergency"
in
is_emergency
I can call it using a custom column like this =emergency([color_column]).
However - my color column contains a lot of extra spaces so I somehow need to call Text.Trim() on the color-parameter. How to write this?
What I thought would work was to just write this:
let
is_emergency = (color as text) =>
color = Text.Trim(color, " "),
if color = "red" or color = "orange" then
"emergency"
else
"not emergency"
in
is_emergency
but this gives me the error Token Literal Expected.
How to write it proper? I am aware I can use the Power Query GUI to create simple functions like this, but my real case is more advanced and I would like to understand the M syntax.
I managed to solve it myself after some research.
let
is_emergency = (color as text) =>
// you need to put the variable declaration inside a new let - in
let
trimmed_color = Text.Trim(color, " "),
// you also need to define the return value and return it in the new let - in
return_value = if trimmed_color = "red" or trimmed_color = "orange" then
"emergency"
else
"not emergency"
in
return_value
in
is_emergency
I am counting values in each window and find the top values and want to save only the top 10 frequent values of each window to hdfs rather than all the values.
eegStreams(a) = KafkaUtils.createStream(ssc, zkQuorum, group, Map(args(a) -> 1),StorageLevel.MEMORY_AND_DISK_SER).map(_._2)
val counts = eegStreams(a).map(x => (math.round(x.toDouble), 1)).reduceByKeyAndWindow(_ + _, _ - _, Seconds(4), Seconds(4))
val sortedCounts = counts.map(_.swap).transform(rdd => rdd.sortByKey(false)).map(_.swap)
ssc.sparkContext.parallelize(rdd.take(10)).saveAsTextFile("hdfs://ec2-23-21-113-136.compute-1.amazonaws.com:9000/user/hduser/output/" + (a+1))}
//sortedCounts.foreachRDD(rdd =>println("\nTop 10 amplitudes:\n" + rdd.take(10).mkString("\n")))
sortedCounts.map(tuple => "%s,%s".format(tuple._1, tuple._2)).saveAsTextFiles("hdfs://ec2-23-21-113-136.compute-1.amazonaws.com:9000/user/hduser/output/" + (a+1))
I can print top 10 as above (commented).
I have also tried
sortedCounts.foreachRDD{ rdd => ssc.sparkContext.parallelize(rdd.take(10)).saveAsTextFile("hdfs://ec2-23-21-113-136.compute-1.amazonaws.com:9000/user/hduser/output/" + (a+1))}
but I get the following error. My Array is not serializable
15/01/05 17:12:23 ERROR actor.OneForOneStrategy:
org.apache.spark.streaming.StreamingContext
java.io.NotSerializableException:
org.apache.spark.streaming.StreamingContext
Can you try this?
sortedCounts.foreachRDD(rdd => rdd.filterWith(ind => ind)((v, ind) => ind <= 10).saveAsTextFile(...))
Note: I didn't test the snippet...
Your first version should work. Just declare #transient ssc = ... where the Streaming Context is first created.
The second version won't work b/c StreamingContext cannot be serialized in a closure.
I am trying to plot yearly data on a geochart. I would like the most recent data on top, but for whatever reason, the earliest year is always on top in the actual visualization.
I have tried re-ordering the table to have the latest years as the first entries in the data with no effect.
I thought that maybe it was happening because I used a view to filter my data, but the filter is not reordering the items with the older ones first (so that shouldn't impact how it is displayed).
I do not want to filter out data since I use transparency to display all points. Here is some sample code that displays the same problem:
function drawVisualization() {
var data = new google.visualization.DataTable();
data.addColumn('number', 'Latitude');
data.addColumn('number', 'Longitude');
data.addColumn('number', 'Color');
data.addColumn('number', 'Output (MW)');
data.addRows([
[35, 135, 2, 334],
[35, 135, 1, 100],
[35.1, 135.1, 1, 100],
[35.1, 135, 1, 100],
[35, 135.1, 1, 100],
[34.9, 134.9, 1, 100],
[34.9, 135, 1, 100],
[35, 135.1, 1, 100],
]);
var geochart = new google.visualization.GeoChart(
document.getElementById('visualization'));
geochart.draw(data, {
colorAxis: {
'minValue': 1,
'maxValue': 2,
'values': [1, 2],
'colors': ['black','red'],
},
'markerOpacity': 0.5,
'region': 'JP'
});
}
I can change the values in column 2 or 3 (0-indexed), or I can change the order of the entries in to the data table, but I keep getting the same result. I have a feeling it always sticks bigger sized values in the back so you can still see the little values, but I'm wondering if there is any authoritative reference on it, or any way to get around it.
This is what it looks like no matter what I do:
What I want it to look like is as follows (manipulated the SVG manually to adjust the Z-order):
I played around with it for a bit, and I think you're right: it's automatically z-indexing the markers in size-order. If I read your intent correctly, you are looking to show some subset of years, and you want the markers to be z-indexed by years. I think you can accomplish that with some custom filtering: sort your data by location and year, then for every location, filter out every year with a smaller size than any of the newer years. Something like this should work:
// order by location and year (descending)
var rows = data.getSortedRows([0, 1, {column: 2, desc: true}]);
// parse the rows backwards, removing all years where a location has a newer year with a larger size value
// we don't need to parse row 0, since that will always be the latest year for some location
var size, lat, long;
for (var i = rows.length - 1; i > 0; i--) {
size = data.getValue(rows[i], 3);
lat = data.getValue(rows[i], 0);
long = data.getValue(rows[i], 1);
for (var j = i - 1; j >= 0 && lat == data.getValue(rows[j], 0) && long == data.getValue(rows[i], 1); j--) {
if (size < data.getValue(rows[j], 3)) {
rows.splice(i, 1);
break;
}
}
}
var view = new google.visualization.DataView(data);
view.setRows(rows);
Here's a working example based on your code: http://jsfiddle.net/asgallant/36AmD/
You are correct that the order of the markers is determined by the size, with the larger markers drawn first so they end up below the smaller markers, which is a convenience for most applications. If you wish to hide 'later' markers based on order, you'll have to do that another way, perhaps by hiding the rows of data.
Is there a reason it makes sense to hide data if it covers 'earlier' data? Perhaps an option could be added to disable this automatic reordering, especially if transparent colors are used to allow you to see through.
Try this, helped me in a project:
setTimeout(function () {
$('.google-visualization-table').css("z-index", "1");
}, 500);