Matplotlib Barh 过渡平滑

Question

I'm a noob when it comes to Matplotlib and visualization in general. I've been following this tutorial: https://thecleverprogrammer.com/2020/06/23/bar-chart-race-tutorial-in-python-with-matplotlib/

Which provides a good base for solving my problems my only issue is the transitions are very abrupt - how would I go about adding smooth transitions like this - this is an example of how the transitions should look don't mind the actual data:

As far as I'm aware - the animation function produces a frame for every interval - how can I get frames where the bars are animating over each other?

Edit:

Here's the code I'm looking at

import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import matplotlib.animation as animation
from matplotlib.offsetbox import OffsetImage, AnnotationBbox
from moviepy.editor import VideoClip
from moviepy.video.io.bindings import mplfig_to_npimage

url = 'https://gist.githubusercontent.com/johnburnmurdoch/4199dbe55095c3e13de8d5b2e5e5307a/raw/fa018b25c24b7b5f47fd0568937ff6c04e384786/city_populations'

df = pd.read_csv(url, usecols=['name', 'group', 'year', 'value'])
df.head(3)

colors = dict(zip(
    ["India", "Europe", "Asia", "Latin America", "Middle East", "North America", "Africa"],
    ["#adb0ff", "#ffb3ff", "#90d595", "#e48381", "#aafbff", "#f7bb5f", "#eafb50"]
))
group_lk = df.set_index('name')['group'].to_dict()

fig, ax = plt.subplots(figsize=(15, 8))


def draw_barchart(current_year):
    dff = df[df['year'].eq(current_year)].sort_values(by='value', ascending=True).tail(10)
    ax.clear()
    ax.barh(dff['name'], dff['value'], color=[colors[group_lk[x]] for x in dff['name']])
    dx = dff['value'].max() / 200
    for i, (value, name) in enumerate(zip(dff['value'], dff['name'])):
        ax.text(value-dx, i,     "   {} ({})".format(name,round(value, 2)),           size=12, color='#777777' ,weight=600, ha='left', va='center')

    ax.text(1, 0.4, current_year, transform=ax.transAxes, color='#777777', size=46, ha='right', weight=800)
    #ax.text(0, 1.06, 'Population (thousands)', transform=ax.transAxes, size=12, color='#777777')
    ax.xaxis.set_major_formatter(ticker.StrMethodFormatter('{x:,.0f}'))
    ax.xaxis.set_ticks_position('bottom')
    ax.tick_params(axis='x', colors='#777777', labelsize=12)
    ax.set_yticks([])
    ax.margins(0, 0.01)
    ax.grid(which='major', axis='x', linestyle='-')
    ax.set_axisbelow(True)
    ax.text(0, 1.15, 'This is a title',
            transform=ax.transAxes, size=24, weight=600, ha='left', va='top', color="#777")
    ax.text(1, 0, "My description here", transform=ax.transAxes, color='#777777', ha='right',
            bbox=dict(facecolor='white', alpha=0.8, edgecolor='white'))
    plt.box(False)
    plt.subplots_adjust(left=0.15, right=0.80, bottom=0.20, top=0.86)
    


fig, ax = plt.subplots(figsize=(15, 8))
plt.show()
animator = animation.FuncAnimation(fig, draw_barchart, frames=range(1900, 2019))
animator.save('linex.gif', dpi=180, writer='imagemagick')

Answer 1

As mentioned in the comments, matplotlib animations do not allow for smooth transitions. It's because the graph is created and played back frame by frame. It doesn't create a graph to complement between frames. If you want to use python for bar chart tracing, there are some good dedicated libraries in python. The name of it is bar_char_race . You can also adjust the details. Depending on the file format, you may need to pre-install ffmpeg or other software.

import pandas as pd
import bar_chart_race as bcr

url = 'https://gist.githubusercontent.com/johnburnmurdoch/4199dbe55095c3e13de8d5b2e5e5307a/raw/fa018b25c24b7b5f47fd0568937ff6c04e384786/city_populations'

df = pd.read_csv(url, usecols=['name', 'group', 'year', 'value'])

df.value = df.value.astype(int)
# top 10 city
dfs = df.groupby(['group','name'],as_index=False)['value'].max().sort_values(by='value', ascending=False).head(10)
top10 = dfs.name[:10].values

dff = df.query('year >= 1900 and name in @top10')
dff = dff.pivot_table(index='year',columns='name', values='value')
dff.fillna(0, axis=1, inplace=True)
dff.index = pd.to_datetime(dff.index, format='%Y')

bcr.bar_chart_race(df=dff, n_bars=10, filename='poptop10.mp4', period_fmt='%Y')