Data mining in knime with a tad of r or a dash of python data science ∪ data engineering gas news

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In this post I try to demonstrate KNIME’s power by presenting a workflow that takes raw data and produces a punchcard chart from it. All of this requires just using the UI and writing 2 lines of R code or a few lines of Python code. At the end of the workflow we’ll have a dataset with 3 columns representing the day, hour and number of messages and we’ll use this dataset to plot a chart similar to GitHub’s punchcard chart. Exploring Slack export

The last part of this section is to transform the individual JSON objects into rows of a dataset. gas and electric credit union For this we will use the JSON Path node. Connect the output of the Loop End node to the input of the JSON Path. Double click on it to edit it. We need to map the object’s properties to a column. This structure is fairly simple to map, just look at the screenshot. electricity balloon experiment You need to use the Add single query button. You’ll notice that subtype is mapped to type. That’s because all the original types are messages. Also, we’ll use the original subtype column to filter out bot’s messages.

Add a Row Filter node to remove the messages that have a set type (which is aliased from subtype). Messages from users have the type set to null, while bot users have a set type. Connect the output from the JSON Path node to the input of the Row Filter node. Double click on it to configure it. Select Include rows by attribute value, select the type column and only missing values match (a.k.a IS NULL).

At this point, some columns are not useful at all, like the type and iteration column (created by the 2nd node), so we’ll just filter them out with the Column Filter node. 3 gases that cause acid rain As usual, connect the output of the Row Filter node to the input of the Column node. Double click on it to configure it. Select Enforce exclusion and add the two obsolete columns.

Create a String Manipulation node and connect its input to the output of the Column Filter node. To be able to retrieve days of the week and hours of the day, we need to transform the timestamp from String to Long to DateTime. We start with the first transformation. Double click on the node to configure it. gas law questions and answers In the Expression text field you need to use the timestamp column and then cast it two times: toLong(toDouble($timestamp$)).

To transform the numerical timestamp to a DateTime column we need to add a UNIX Timestamp to Date&Time. We connect its input to the output of the String Manipulation node. Double click on it to edit it. Make sure the Include selection has timestamp in it, and only timestamp. We’ll overwrite the timestamp column with the new values, so select Replace selected columns. The timestamp unit in this case is Seconds and we want the New type to be Date&Time.

Let’s start with the hour of the day. Connect the output of the Sorter node to the input of the first Date&Time to String node. Double click on it to edit it. x men electricity mutant The include section should only have timestamp in it. Append a new column with the _hour suffix. The format of the new column should be set to HH (the 24 hour format). gas vs electric stove The locale should probably be set to en_US.

For the day of the week, create another Date&Time to String node that will have its input connected to the output of the first Date&Time to String node. Double click on it to customise it. The include section should only have timestamp in it. Append a new column with the _day suffix. The format of the new column should be set to c (the Sunday first numerical format for the weekday). electricity invented The locale should be set to en. Unfortunately, I wan not able to find an easy way to have a Monday first format.

It is easier if we work with numerical data in the charts so we will just convert timestamp_hour and timestamp_day to numerical values. For this, use a String to Number node that receives as input the output of the second Date&Time to String node. Double click on it to customise it and make sure only the timestamp_hour and timestamp_day are in the Include section. The Type should be double.

The last data related step is the aggregation. We will use a Group By node which receives as input the output from the String to Number node. Double click on it to edit it. In the Groups tab, have timestamp_hour and timestamp_day in the Group column(s) section. Column naming should be Aggregation method(column name). astrid y gaston lima menu prices In the Manual Aggregation tab, from the Available columns select timestamp and change the Aggregation (click to change) from First to Count. Visualisation