In a Plotly histogram, how to make each animation frame a row in the dataframe?

Question

I have the following pandas dataframe:

       month  stories  comments  comment_authors  story_authors
0    2006-10       49        12                4             16
1    2007-02      564       985              192            163
2    2007-03     1784      4521              445            287

I am trying to construct a Plotly histogram where there are four categorical bins (x-axis) for each of the stories , comments , comment_authors , and story_authors columns, and the count (y-axis) is the given quantity for a specific month (ie a specific row). I am then trying to animate the histogram based on month in Plotly Express using animation_frame and animation_group .

For example, the first histogram for month=2006-10 would look something like:

50 |  ____
45 | |    |
40 | |    |
35 | |    |
30 | |    |
25 | |    |
20 | |    |
15 | |    |                               ____
10 | |    |    ____                      |    |
 5 | |    |   |    |    ______           |    |
 0  ----------------------------------------------------
     stories  comments  comment_authors  story_authors

In the histogram for the next animation frame, it would read the values from the stories , comments , comment_authors , story_authors columns for month=2007-02 .

Is this possible to construct in Plotly? Is there a better figure to use than px.Histogram , like px.Bar ? I have tried putting the columns on the x-axis and using the month for the animation frame, but this stacks the columns into one bin on the histogram and uses the count of the entire column, not a specific row's value.

histogram = dcc.Graph(figure=px.histogram(
    df, x=['stories', 'comments', 'comment_authors', 'story_authors'],
    animation_frame='month', animation_group='month'
))

Answer 1

It is not possible to draw a histogram with the data you are presenting. The best you can do is a bar chart, and you can animate it with a time series. I have modified the sample in the official reference to fit your data.

import pandas as pd
import numpy as np
import io

data = '''
      month  stories  comments  comment_authors  story_authors
0    2006-10       49        12                4             16
1    2007-02      564       985              192            163
2    2007-03     1784      4521              445            287
'''

df = pd.read_csv(io.StringIO(data), delim_whitespace=True)
df.set_index('month', inplace=True)
dfs = df.unstack().reset_index()
dfs.columns = ['category', 'month', 'value']
import plotly.express as px

fig = px.bar(dfs, x='category', y='value', color='category', animation_frame='month', range_y=[0,dfs['value'].max()])

fig.show()

Answer 2

@r-beginners' answer is the best way to do this, but I wanted to share how to do it manually in case anyone else finds this question in the future (and so my toil doesn't go to waste). Here is how I was accomplishing this manually before @r-beginners' answer.

# build list of frames for animation
cols = ['stories', 'comments', 'comment_authors', 'story_authors']
frames = list(map(
    lambda index: go.Frame(
        data=[go.Bar(
            x=cols,
            y=list(map(lambda col: df.iloc[index][col], cols))
        )]
    ), range(len(df.index))
))

# compute chart height
m = max(list(filter(
    lambda m: not isinstance(m, str), list(df.max())
))) * 1.1

# compute animation steps for slider
steps = list(map(
    lambda index: {
        'args': [
            [str(df.iloc[index]['month'])],
            {
                'frame': {'duration': 300, 'redraw': False},
                'mode': 'immediate',
                'transition': {'duration': 300}
            }
        ],
        'label': str(df.iloc[index]['month']),
        'method': 'animate'
    }, range(len(df.index))
))

# metadata for slider element
sliders_dict = {
    "active": 0,
    "yanchor": "top",
    "xanchor": "left",
    "currentvalue": {
        "font": {"size": 20},
        "prefix": "Month: ",
        "visible": True,
        "xanchor": "right"
    },
    "transition": {"duration": 300, "easing": "cubic-in-out"},
    "pad": {"b": 10, "t": 50},
    "len": 0.9,
    "x": 0.1,
    "y": 0,
    "steps": steps
}

# histogram figure - actually a bar chart
histogram = dcc.Graph(id='counts-histogram', figure=go.Figure(
    data=frames[0].data[0],
    layout=go.Layout(
        yaxis=dict(range=[0, m], autorange=False),
        updatemenus=[
            {
                "buttons": [
                    {
                        "args": [None, {"frame": {"duration": 500, "redraw": False},
                                        "fromcurrent": True, "transition": {"duration": 300,
                                                                            "easing": "quadratic-in-out"}}],
                        "label": "Play",
                        "method": "animate"
                    },
                    {
                        "args": [[None], {"frame": {"duration": 0, "redraw": False},
                                          "mode": "immediate",
                                          "transition": {"duration": 0}}],
                        "label": "Pause",
                        "method": "animate"
                    }
                ],
                "direction": "left",
                "pad": {"r": 10, "t": 87},
                "showactive": False,
                "type": "buttons",
                "x": 0.1,
                "xanchor": "right",
                "y": 0,
                "yanchor": "top"
            }
        ],
        sliders = [sliders_dict]
    ),
    frames=frames
))