Python 中的可视化熊猫

Question

嘿 Whosebug 团队，

我有以下问题。

我从两个 table 中创建了一个 table，其中包含以下列：

Index(['state_name', 'overall_outcome', 'date', 'new_results_reported',
       'total_results_reported', 'Population_2019'],
      dtype='object')

但现在每个州都列出了 12 倍，我创建了一个数据透视表，准确总结了一年的所有内容。只是现在缺少 Population_2019 值，我也想以图形方式添加。

pivot_df = Amerika3.pivot_table(index='state_name' , columns='Month', values='new_results_reported', aggfunc='sum')
print(pivot_df)

我现在的问题是如何创建一个图表来显示 state_name、Population_2019、new_results_reported 以及相应月份的图表。

在图表中，我想看到例如在阿拉巴马州，第 1、2、3 个月有 'x' 个案例....与阿拉巴马州的人口相比报告

my created table's

    {'state_name': ['Alabama',
  'Alabama',
  'Alabama',
  'Alabama',
  'Alabama',
  'Alabama',
  'Alabama',
  'Alabama',
  'Alabama',
  'Alabama',
  'Alabama',
  'Alabama',
  'Alaska',
  'Alaska',
  'Alaska',
  'Alaska',
  'Alaska',
  'Alaska',
  'Alaska',
  'Alaska',
  'Alaska',
  'Alaska',
  'Alaska',
  'Alaska'],
 'Month': [1,
  2,
  3,
  4,
  5,
  6,
  7,
  8,
  9,
  10,
  11,
  12,
  1,
  2,
  3,
  4,
  5,
  6,
  7,
  8,
  9,
  10,
  11,
  12],
 'Population_2019': [4903185.0,
  4903185.0,
  4903185.0,
  4903185.0,
  4903185.0,
  4903185.0,
  4903185.0,
  4903185.0,
  4903185.0,
  4903185.0,
  4903185.0,
  4903185.0,
  731545.0,
  731545.0,
  731545.0,
  731545.0,
  731545.0,
  731545.0,
  731545.0,
  731545.0,
  731545.0,
  731545.0,
  731545.0,
  731545.0],
 'new_results_reported': [446366,
  322959,
  272495,
  298138,
  316494,
  270164,
  452655,
  436392,
  376831,
  432346,
  400787,
  554491,
  235778,
  199990,
  224981,
  221276,
  154334,
  81092,
  150296,
  175596,
  158323,
  221439,
  296043,
  261463],
 'test_rate_in_Procent': [9.103592868716968,
  6.586718632888622,
  5.557510067435759,
  6.0804966567649394,
  6.454865561874577,
  5.509969540207028,
  9.23185643617363,
  8.900174070527626,
  7.685433039952602,
  8.817656278521003,
  8.174013421888016,
  11.308792142250395,
  32.23014305340068,
  27.338031153244163,
  30.75422564572241,
  30.247763295491048,
  21.096993349691406,
  11.085032363012528,
  20.545010901585,
  24.00344476416352,
  21.64227764525764,
  30.27004490496142,
  40.46818719285895,
  35.74120525736626]}

Answer 1

使用您提供的示例数据
select 您要绘制的变量... new_results_reported 因此使用 .loc[] 所以 unstack() 会产生预期的 12列不是 24...
重塑它以进行绘图 - 我更喜欢使用 unstack() 而不是 pivot()。 Population_2019 保留在索引中以启用此
然后用每月数据和州数据的不同表示来绘制它就很简单了


import pandas as pd
import numpy as np
import plotly.express as px
import plotly.graph_objects as go


Amerika2 = pd.DataFrame({"state_name": ["Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alabama", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska", "Alaska"], 
                         "Month": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], 
                         "Population_2019": [4903185.0, 4903185.0, 4903185.0, 4903185.0, 4903185.0, 4903185.0, 4903185.0, 4903185.0, 4903185.0, 4903185.0, 4903185.0, 4903185.0, 731545.0, 731545.0, 731545.0, 731545.0, 731545.0, 731545.0, 731545.0, 731545.0, 731545.0, 731545.0, 731545.0, 731545.0], 
                         "new_results_reported": [446366, 322959, 272495, 298138, 316494, 270164, 452655, 436392, 376831, 432346, 400787, 554491, 235778, 199990, 224981, 221276, 154334, 81092, 150296, 175596, 158323, 221439, 296043, 261463], 
                         "test_rate_in_Procent": [9.103592868716968, 6.586718632888622, 5.557510067435759, 6.0804966567649394, 6.454865561874577, 5.509969540207028, 9.23185643617363, 8.900174070527626, 7.685433039952602, 8.817656278521003, 8.174013421888016, 11.308792142250395, 32.23014305340068, 27.338031153244163, 30.75422564572241, 30.247763295491048, 21.096993349691406, 11.085032363012528, 20.545010901585, 24.00344476416352, 21.64227764525764, 30.27004490496142, 40.46818719285895, 35.74120525736626]
                        })

df = (
    Amerika2.loc[:,["state_name","Month","Population_2019","new_results_reported"]]
    .set_index(["state_name", "Month", "Population_2019"])
    .unstack("Month")
    .droplevel(0, 1)
)

# create figure of monthly values
fig = px.bar(df.reset_index(), x="state_name", y=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])

# add a trace that is state population
fig.add_trace(
    go.Scatter(
        x=df.index.get_level_values("state_name"),
        y=df.index.get_level_values("Population_2019"),
        yaxis="y2",
        name="population",
    )
)
fig.update_layout({"yaxis2": {"anchor": "x", "overlaying": "y", "side": "right"}})

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