one-graph | OneGraph Database | Database library

With only two bars, it's fairly easy. The solution is to align the bars on the "edge" of the tick, one bar is aligned to the left, the other to the right.

Repeat the same logic for proper alignment of the annotations. Half of them are left-aligned, the others are right-aligned

Let's use pandas plot it is easier:

Like the other issues you mentioned (such as the missing parentheses in print, and the items to iteritems change), this is a Python version issue. In Python 3, pop doesn't work on dict_keys.

To work around this, you can make it a list. In your code, do nodes = list(graph.keys()).

umap[value] = newNode; exhibits undefined behavior, by way of accessing an uninitialized variable value.

In practice, value contains some garbage that happens to sit on the stack. Changes to seemingly unrelated parts of the program affect the contents of the stack, and thereby the initial value of value, and ultimately the way the aforementioned undefined behavior manifests itself.

You can get the series name from ev.target.dataItem.dataContext.name, which is documented further down in the same page. You can use that and loop through the chart series array and call show() or hide() as needed on matching/non-matching series, similar to the v3 demo:

Quicksort is known to exhibit poor performance when the input set contains lots of duplicates. The solution is to use three-way partitioning as described on Wikipedia:

Repeated elements

With a partitioning algorithm such as the ones described above (even with one that chooses good pivot values), quicksort exhibits poor performance for inputs that contain many repeated elements. The problem is clearly apparent when all the input elements are equal: at each recursion, the left partition is empty (no input values are less than the pivot), and the right partition has only decreased by one element (the pivot is removed). Consequently, the algorithm takes quadratic time to sort an array of equal values.

To solve this problem (sometimes called the Dutch national flag problem), an alternative linear-time partition routine can be used that separates the values into three groups: values less than the pivot, values equal to the pivot, and values greater than the pivot. ... The values equal to the pivot are already sorted, so only the less-than and greater-than partitions need to be recursively sorted. In pseudocode, the quicksort algorithm becomes

What I'm doing is dynamically labeling the bar graphs based on the coordinates for each patch that's drawn by the bar function.

Well yes, that is indeed what the bazel build command does.

If you look at the actual BUILD file (tensorflow/tools/graph_transform/BUILD) you'll see that it has its build rules and dependencies, which basically includes all the source code in that directory. The summarize_graph command's logic is included in those (you'll find that in summarize_graph_main.cc under the same directory).

You can follow the specific build rule to see what it does, or use a visualization tool. Here's what it looks like:

Here is a JS callback version for Standalone Document (tested on Bokeh 1.0.4):