[Draw a race motion with several lines of pandas_alive code] 1. Bar Chart (Test Code + Dataset + Drawing Parameter Resolution)

Welcome to your attention Column "pandas_alive Mapping Contest" , continuously updating
Welcome to your attention Column "pandas_alive Mapping Contest" , continuously updating

Resource file download:
Column Learning Instructions (Configured venv Virtual Environment + Ready-to-Use Test Code + Test Dataset + Parameter api parsing)

All Effects Preview:
Effect Graphics Display (Configured venv Virtual Environment + Ready-to-Use Test Code + Test Dataset + Parameter api parsing)

Environment Configuration:
Environment Configuration and Detection (Configured venv Virtual Environment + Ready-to-Use Test Code + Test Dataset + Parameter api Resolution)

1. Bar chart

Bar chart API description:

df.fillna(0).plot_animated('1.horizontal bar.gif', period_fmt='%Y-%m-%d'),
title='Find you've gone far - 1. Horizontal Bar', fixed_max=True,
fixed_order=True)
Df. Fillna(0). Plot_ Animated (parameter 1, period_fmt='%Y-%m-%d'),
title='Find you've gone far - 1. Horizontal Bar', fixed_max=True,
fixed_order=True)

Parameter 1 generates the picture name. gif

period_fmt="%Y-%m-%d %H:%M:%S"
Format to 2022-01-12 5:30:00, optionally omit the default to indicate that the formatting time output is in the lower right corner of the picture

Fixed_ Does Max fix the background bar in the background image
True Fixed Background Bar

false does not fix the background bar in the background image

Fixed_ Whether order fixes competitor entries or not means whether the ranks of individual competitors will change

True Fixed Competitor Entry
false Fixed Competitor Entry

orientation='h'
orientation='v'
Is the direction of the bar graph horizontal or vertical

h level (default)
v Vertical

perpendicular_bar_func='max'
Add a shaded section of all data to assist viewing

max shadow part value is maximum
mean shaded part value is average
min Shadow part value is minimum

Bar Chart Dataset

Save as file Aus_Elec_Gen_1980_2018.csv usage, recommended download via code cloud

,  Black coal,  Brown coal,  Natural gas,  Oil products,  Other a,  Biomass,  Wind,  Hydro,Large-scale solar PV,  Small-scale solar PV,  Geothermal
1989,87573.00,33594.00,14359.00,3552.00,,750.00,,14880.00,,,
1990,89511.00,36048.00,10772.00,3396.00,,769.00,,16103.00,,,
1991,94325.10,34559.00,11633.00,2362.00,,670.00,,15768.00,,10.90,
1992,97872.70,33248.00,12295.00,2421.00,,670.00,,16953.00,,13.30,
1993,100544.10,34890.00,12199.00,2320.00,,670.00,4.00,16649.00,,15.90,
1994,102522.10,35832.00,14913.00,2738.00,,723.00,7.00,16239.00,,18.90,
1995,106089.60,39427.00,12445.00,2805.00,,928.00,7.00,15731.00,,23.40,
1996,109452.20,41893.00,11426.00,2175.00,,965.00,7.00,16852.00,,27.80,
1997,116969.50,46633.00,12934.00,1821.00,,1029.00,8.00,15733.00,,33.50,
1998,118586.30,49703.00,16001.00,1729.00,,1133.00,28.00,16563.00,,37.70,
1999,123833.50,50200.00,16245.00,1784.00,,1134.00,58.00,16720.00,,43.50,
2000,134264.00,52223.00,17271.00,2044.00,,645.00,210.00,16933.00,,50.00,
2001,116774.70,56493.00,31730.00,2446.00,,950.00,364.00,16054.00,,58.30,
2002,115296.60,55160.30,29375.30,1661.00,1792.20,1583.60,703.10,16490.00,,58.30,
2003,121182.30,55572.80,30919.40,1388.70,1817.00,1799.50,705.00,16331.10,,68.10,0.50
2004,127788.50,53377.80,23802.90,2841.00,434.00,3830.00,885.00,15612.20,,77.80,0.50
2005,130231.60,54552.80,22725.90,3058.00,517.00,3911.00,1713.10,16029.20,,90.30,0.50
2006,132368.50,54375.80,31849.90,2893.00,479.00,3953.00,2611.10,14517.00,,104.70,0.50
2007,129569.30,54658.70,34955.80,4058.00,106.00,4596.00,3093.10,12056.90,,122.80,0.50
2008,127270.50,56981.40,37660.40,3388.00,3579.90,2795.20,3823.80,11869.40,,155.60,0.50
2009,123724.50,56068.30,44585.40,3106.80,2991.00,2777.40,5051.70,13548.70,,424.90,0.50
2010,116948.80,55298.10,48996.20,3093.80,2716.10,2101.70,6084.90,16806.70,,1530.40,0.50
2011,116654.40,55067.70,48571.60,2702.50,1088.10,3043.75,6969.70,14083.30,,2558.70,0.50
2012,111491.10,47555.10,51053.40,4464.30,1945.30,3143.50,7959.60,18269.60,,3826.30,0.50
2013,106965.50,46076.20,54393.90,5012.40,,3499.39,10252.00,18421.00,49.68,4366.28,0.50
2014,107639.40,50970.30,52916.91,6828.45,,3592.23,11466.60,13445.00,107.22,5424.11,0.60
2015,114294.98,48795.86,50536.08,5655.62,,3789.89,12199.50,15318.18,457.21,6381.05,0.22
2016,118272.30,43557.76,50459.75,5272.59,,3500.55,12596.99,16284.89,672.40,7399.26,0.50
2017,121592.60,36067.00,53839.39,5262.60,,3534.09,14989.42,15838.82,1007.58,8922.36,

1.1 Horizontal Bar Routine

# @Time    : 2022/1/12 11:46
# @Author: Nanli
# @FileName: 1.1 horizontal bar. py
import pandas as pd
import pandas_alive

######Show Chinese Song font import, if using Chinese plus this code######
import matplotlib as plt

plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
#####################################################

df = pd.read_csv("data source data/Aus_Elec_Gen_1980_2018.csv", index_col=0, parse_dates=[0], thousands=',')

df.fillna(0).plot_animated('1.1 Horizontal Bar Graph.gif', period_fmt="%Y-%m-%d",
                           title='Find you're far away - 1.1 Horizontal Bar Graph', fixed_max=False,
                           perpendicular_bar_func='mean',
                           fixed_order=False)

1.2 Vertical bar routine

# @Time    : 2022/1/12 13:24
# @Author: Nanli
# @FileName: 1.2 vertical bar chart. py
import pandas_alive
import pandas as pd

######Show Chinese Song font import, if using Chinese plus this code######
import matplotlib as plt

plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
#####################################################

df = pd.read_csv("data source data/Aus_Elec_Gen_1980_2018.csv", index_col=0, parse_dates=[0], thousands=',')

df.plot_animated(filename='1.2 Vertical bar chart.gif', title='Find you're far away - 1.2 Vertical bar chart',perpendicular_bar_func='min', orientation='v')

summary

Found that you are far away from the original @mzh work, reprinting must label the original link

Crated: 2022-1-13

I've been working around for a week, combing out a lot of ways to get started with small white lightning protection, and will continue to update, if you see it helpful, I hope you will get some approval 👍 Collection support! (After all, it's too difficult to finish in a short time, so I suggest putting it in my favorite folder to gray up)

Keywords: Python data visualization

Added by kigroy on Tue, 18 Jan 2022 04:01:20 +0200

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