WIP bubble chart

bubble_chart.py

@@ -0,0 +1,158 @@
+#!/usr/bin/env python3
+
+import os
+
+import csv
+
+from typing import Any
+
+# file = "/home/marc/Dokumente/v0.0.1a2-data-1666552071.csv"
+file = r"C:\Users\marc.friemelt\Nextcloud\Dokumente\v0.0.1a2-data-1666552071.csv"
+
+content = {}
+
+# Create dict from csv file
+# Key names are the ones used in the csv file
+with open(file, "r") as f:
+    reader = csv.reader(f)
+    headers = next(reader)
+    for row in reader:
+        codec_preset = " ".join([row[0], row[2]])
+        try:
+            content[codec_preset]
+        except KeyError:
+            content[codec_preset] = []
+        # NOTE | to merge dicts requires python 3.9 or newer
+        content[codec_preset].append(
+            {"CRF": row[1]}
+            | {"Input file": row[3]}
+            | {"Output file size (MiB)": row[4]}
+            | {"Encode time (s)": row[5]}
+            | {"VMAF Score (mean)": row[6]}
+            | {"VMAF Score (min)": row[7]}
+        )
+
+print(content)
+
+exit()
+
+import plotly.graph_objects as go
+import plotly.express as px
+
+# Load data, define hover text and bubble size
+data = px.data.gapminder()
+df_2007 = data[data["year"] == 2007]
+df_2007 = df_2007.sort_values(["continent", "country"])
+
+"""
+hover_text = []
+bubble_size = []
+
+for index, row in df_2007.iterrows():
+    hover_text.append(
+        (
+            "Country: {country}<br>"
+            + "Life Expectancy: {lifeExp}<br>"
+            + "GDP per capita: {gdp}<br>"
+            + "Population: {pop}<br>"
+            + "Year: {year}"
+        ).format(
+            country=row["country"],
+            lifeExp=row["lifeExp"],
+            gdp=row["gdpPercap"],
+            pop=row["pop"],
+            year=row["year"],
+        )
+    )
+    bubble_size.append(math.sqrt(row["pop"]))
+
+df_2007["text"] = hover_text
+df_2007["size"] = bubble_size
+sizeref = 2.0 * max(df_2007["size"]) / (100**2)
+"""
+
+# Dictionary with dataframes for each continent
+continent_names = ["Africa", "Americas", "Asia", "Europe", "Oceania"]
+continent_data = {
+    continent: df_2007.query("continent == '%s'" % continent)
+    for continent in continent_names
+}
+
+# Create figure
+fig = go.Figure()
+
+for continent_name, continent in continent_data.items():
+    fig.add_trace(
+        go.Scatter(
+            x=continent["gdpPercap"],
+            y=continent["lifeExp"],
+            name=continent_name,
+            # text=continent["text"],
+            # marker_size=continent["size"],
+        )
+    )
+
+# Tune marker appearance and layout
+fig.update_traces(
+    # mode="markers", marker=dict(sizemode="area", sizeref=sizeref, line_width=2)
+    mode="markers"
+)
+
+fig.update_layout(
+    title="Graph title",
+    xaxis=dict(
+        title="X-Axis",
+        gridcolor="white",
+        # type="log",
+        gridwidth=2,
+    ),
+    yaxis=dict(
+        title="Y-Axis",
+        gridcolor="white",
+        gridwidth=2,
+    ),
+    # paper_bgcolor="rgb(243, 243, 243)",
+    # plot_bgcolor="rgb(243, 243, 243)",
+)
+# fig.show()
+
+fig = go.Figure()
+
+# NOTE explicit convertion to integer necessary
+max_x = max(int(line["Encode time (s)"]) for line in content)
+max_y = max(float(line["Output file size (MiB)"]) for line in content)
+
+x_axis = list(line["Encode time (s)"] for line in content)
+y_axis = list(line["Output file size (MiB)"] for line in content)
+
+for line in content:
+    fig.add_trace(
+        go.Scatter(
+            x=x_axis,
+            # x=list(range(0, max_x)),
+            # x=line["Encode time (s)"],
+            y=y_axis,
+            # y=list(range(0, int(max_y))),
+            # y=line["Output file size (MiB)"],
+            name=line["Codec Preset"],
+        )
+    )
+
+fig.update_traces(mode="markers")
+
+fig.update_layout(
+    title="Graph title",
+    xaxis=dict(
+        title="X-Axis",
+        gridcolor="white",
+        # type="log",
+        gridwidth=2,
+    ),
+    yaxis=dict(
+        title="Y-Axis",
+        gridcolor="white",
+        gridwidth=2,
+    ),
+)
+
+fig.show()

requirements.txt

@@ -1 +1,2 @@
 ffmpy>=0.3.0
+plotly