如何在单个ytick上绘制散点图

Question

我只是想知道是否有任何python包可以用来绘制单轴上的散点图。我对新的想法和方法持开放态度，想在开始之前试探一下

可以用Python绘制上面的图吗？如果可以，将使用哪个包绘制上面的图？有人能解释一下用Python绘制上面的图吗？我很高兴收到你的任何线索

示例集：

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'2009/9/18 15:00', '2009/9/18 19:00', '2009/9/18 21:00', '2009/9/18 23:00', '2009/9/19 3:00', '2009/9/19 5:00', '2009/9/19 7:00', '2009/9/19 11:00', '2009/9/19 15:00', '2009/9/19 19:00', '2009/9/19 21:00', '2009/9/19 23:00', '2009/9/20 3:00', '2009/9/20 5:00', '2009/9/20 7:00', '2009/9/20 11:00', '2009/9/20 15:00', '2009/9/20 19:00', '2009/9/20 21:00', '2009/9/20 23:00', '2009/9/21 3:00', '2009/9/21 5:00', '2009/9/21 7:00', '2009/9/21 11:00', '2009/9/21 15:00', '2009/9/21 19:00', '2009/9/21 21:00', '2009/9/21 23:00', '2009/9/22 3:00', '2009/9/22 5:00', '2009/9/22 7:00', '2009/9/22 11:00', '2009/9/22 15:00', '2009/9/22 19:00', '2009/9/22 21:00', '2009/9/22 23:00', '2009/9/23 3:00', '2009/9/23 5:00', '2009/9/23 7:00', '2009/9/23 11:00', '2009/9/23 15:00', '2009/9/23 19:00', '2009/9/23 21:00', '2009/9/23 23:00', '2009/9/24 3:00', '2009/9/24 5:00', '2009/9/24 7:00', '2009/9/24 11:00', '2009/9/24 15:00', '2009/9/24 19:00', '2009/9/24 21:00', '2009/9/24 23:00', '2009/9/25 3:00', '2009/9/25 5:00', '2009/9/25 7:00', '2009/9/25 11:00', '2009/9/25 15:00', '2009/9/25 19:00', '2009/9/25 21:00', '2009/9/25 23:00', '2009/9/26 3:00', '2009/9/26 5:00', '2009/9/26 7:00', '2009/9/26 11:00', '2009/9/26 15:00', '2009/9/26 19:00', '2009/9/26 21:00', '2009/9/26 23:00', '2009/9/27 3:00', '2009/9/27 5:00', '2009/9/27 7:00', '2009/9/27 11:00', '2009/9/27 15:00', '2009/9/27 19:00', '2009/9/27 21:00', '2009/9/27 23:00', '2009/9/28 3:00', '2009/9/28 5:00', '2009/9/28 7:00', '2009/9/28 11:00', '2009/9/28 15:00', '2009/9/28 19:00', '2009/9/28 21:00', '2009/9/28 23:00', '2009/9/29 3:00', '2009/9/29 5:00', '2009/9/29 7:00', '2009/9/29 11:00', '2009/9/29 15:00', '2009/9/29 19:00', '2009/9/29 21:00', '2009/9/29 23:00', '2009/9/30 3:00', '2009/9/30 5:00', '2009/9/30 7:00', '2009/9/30 11:00', '2009/9/30 15:00', '2009/9/30 19:00', '2009/9/30 21:00', '2009/9/30 23:00', '2009/10/1 3:00', '2009/10/1 5:00', '2009/10/1 7:00', '2009/10/1 11:00', '2009/10/1 15:00', '2009/10/1 19:00', '2009/10/1 21:00', '2009/10/1 23:00', '2009/10/2 3:00', '2009/10/2 5:00', '2009/10/2 7:00', '2009/10/2 11:00', '2009/10/2 15:00', '2009/10/2 19:00', '2009/10/2 21:00', '2009/10/2 23:00', '2009/10/3 3:00', '2009/10/3 5:00', '2009/10/3 7:00', '2009/10/3 11:00', '2009/10/3 15:00', '2009/10/3 19:00', '2009/10/3 21:00', '2009/10/3 23:00', '2009/10/4 3:00', '2009/10/4 5:00', '2009/10/4 7:00', '2009/10/4 11:00', '2009/10/4 15:00', '2009/10/4 19:00', '2009/10/4 21:00', '2009/10/4 23:00', '2009/10/5 3:00', '2009/10/5 5:00', '2009/10/5 7:00', '2009/10/5 11:00', '2009/10/5 15:00', '2009/10/5 19:00', '2009/10/5 21:00', '2009/10/5 23:00', '2009/10/6 3:00', '2009/10/6 5:00', '2009/10/6 7:00', '2009/10/6 11:00', '2009/10/6 15:00', '2009/10/6 19:00', '2009/10/6 21:00', '2009/10/6 23:00', '2009/10/7 3:00', '2009/10/7 5:00', '2009/10/7 7:00', '2009/10/7 11:00', '2009/10/7 15:00', '2009/10/7 19:00', '2009/10/7 21:00', '2009/10/7 23:00', '2009/10/8 3:00', '2009/10/8 5:00', '2009/10/8 7:00', '2009/10/8 11:00', '2009/10/8 15:00', '2009/10/8 19:00', '2009/10/8 21:00', '2009/10/8 23:00', '2009/10/9 3:00', '2009/10/9 5:00', '2009/10/9 7:00', '2009/10/9 11:00', '2009/10/9 15:00', '2009/10/9 19:00', '2009/10/9 21:00', '2009/10/9 23:00', '2009/10/10 3:00', '2009/10/10 5:00', '2009/10/10 7:00', '2009/10/10 11:00', '2009/10/10 15:00', '2009/10/10 19:00', '2009/10/10 21:00', '2009/10/10 23:00', '2009/10/11 3:00', '2009/10/11 5:00', '2009/10/11 7:00', '2009/10/11 11:00', '2009/10/11 15:00', '2009/10/11 19:00', '2009/10/11 21:00', '2009/10/11 23:00', '2009/10/12 3:00', '2009/10/12 5:00', '2009/10/12 7:00', '2009/10/12 11:00', '2009/10/12 15:00', '2009/10/12 19:00', '2009/10/12 21:00', '2009/10/12 23:00', '2009/10/13 3:00', '2009/10/13 5:00', '2009/10/13 7:00', '2009/10/13 11:00', '2009/10/13 15:00', '2009/10/13 19:00', '2009/10/13 21:00', '2009/10/13 23:00', '2009/10/14 3:00', '2009/10/14 5:00', '2009/10/14 7:00', '2009/10/14 11:00', '2009/10/14 15:00', '2009/10/14 19:00', '2009/10/14 21:00', '2009/10/14 23:00', '2009/10/15 3:00', '2009/10/15 5:00', '2009/10/15 7:00', '2009/10/15 11:00', '2009/10/15 15:00', '2009/10/15 19:00', '2009/10/15 21:00', '2009/10/15 23:00', '2009/10/16 3:00', '2009/10/16 5:00', '2009/10/16 7:00', '2009/10/16 11:00', '2009/10/16 15:00', '2009/10/16 19:00', '2009/10/16 21:00', '2009/10/16 23:00', '2009/10/17 3:00', '2009/10/17 5:00', '2009/10/17 7:00', '2009/10/17 11:00', '2009/10/17 15:00', '2009/10/17 19:00', '2009/10/17 21:00', '2009/10/17 23:00', '2009/10/18 3:00', '2009/10/18 5:00', '2009/10/18 7:00']

import pandas as pd

df = pd.DataFrame({'Timestamp': timeData})

df["Timestamp"] = pd.to_datetime(df["Timestamp"], format="%Y/%m/%d %H:%M")



df['hours'] = df["Timestamp"].dt.strftime('%I%p').str.lower().str.lstrip('0')
df['days']  = df["Timestamp"].dt.day_name()

df = pd.crosstab(df['days'], df['hours']).reindex(index=df['days'].unique(), columns=df['hours'].unique())

df

hours   5am 7am 9am 1pm 3pm 5pm 9pm 1am 11am    7pm 11pm    6am 10am    2pm 4pm 6pm 10pm    12am    3am 4am 8am 12pm    8pm
days                                                                                            
Friday  18  14  6   6   17  6   18  4   12  13  15  0   0   0   0   0   0   1   13  0   0   0   0
Saturday    17  14  5   5   17  5   17  5   12  12  15  1   1   1   0   1   1   0   12  1   0   0   1
Sunday  19  15  6   6   18  6   18  6   12  12  16  0   0   0   0   0   0   0   13  0   0   0   0
Monday  18  14  6   6   18  6   18  6   12  12  16  0   0   0   0   0   0   0   12  0   0   0   0
Tuesday 16  14  5   4   17  5   16  6   13  13  16  1   1   1   1   1   1   0   12  0   0   0   0
Wednesday   16  14  4   4   16  5   16  3   14  14  15  0   0   0   0   0   0   1   13  0   0   0   0
Thursday    16  14  4   5   17  4   17  6   13  13  16  0   0   0   1   1   0   0   12  1   1   1   1

Answer 1

• 更新：为什么选择黑色/灰色配色方案。我在黑暗模式下看得很清楚。采样图必须是透明的，因此它看起来是黑色/灰色的。当我看到手机上的问题时，我才意识到情况并非如此，因为手机没有设置为使用如此黑暗的模式。需要更改的内容在代码中很明显，我没有时间更改答案
• 使用^{}
  • 使用sizes=(50, 1000)调整气泡大小。其中0的大小为50，最大值的大小为1000。将50更改为0以获取0值的0大小
• 使用示例数据帧df到.crosstab之前的点
  • hours应该在索引上，因为索引成为x轴
• 按照代码中的注释设置变量轴和图形参数，以生成所需的绘图

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

# beginning with your dataframe before doing the crosstab, create the crosstab as follows
ct = pd.crosstab(df.hours, df.days)

# the data is missing anything for 2am add that to ct as 0s
missing = pd.DataFrame({'Friday': [0], 'Monday': [0], 'Saturday': [0], 'Sunday': [0], 'Thursday': [0], 'Tuesday': [0], 'Wednesday': [0]}, index=['2am'])
ct = ct.append(missing)

# sorted column and axis values
hours = ['5am', '6am', '7am', '8am', '9am', '10am', '11am', '12am', '1pm', '2pm', '3pm', '4pm', '5pm', '6pm', '7pm', '8pm', '9pm', '10pm', '11pm', '12pm', '1am', '2am', '3am', '4am']
days = ['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday', 'Saturday']

# colors for plots
colors = ['purple', 'lime', 'yellow', 'red', 'blue', 'green', 'orange']

# reorder the index and columns
ct = ct.loc[hours, days]

# create the figure
fig, axes = plt.subplots(nrows=7, figsize=(14, 7), facecolor='black', constrained_layout=1)

# iterate through days, axes, and colors
for col, ax, color in zip(days, axes, colors):
    # select data
    data = ct[col].reset_index()
    
    # plot
    sns.scatterplot(data=data, x='index', y=[0]*len(data), size=col, ax=ax, color=color, legend=False, ec='none', sizes=(50, 1000), palette='muted', alpha=0.5)

    # Hide the right and top spines
    ax.spines['right'].set_visible(False)
    ax.spines['top'].set_visible(False)

    # set the y-tick name
    ax.set_yticks([0])
    ax.set_yticklabels([col])

    # remove the x-axis label
    ax.set_xlabel('')

    # set the x margin
    ax.margins(x=0.02)

    # set the plot facecolor
    ax.set_facecolor('black')
    
    # set axis labels, ticklabels and tick colors
    ax.tick_params(colors='gray', which='both')

    # set spine color
    ax.spines['bottom'].set(color='gray')

display(ct)

      Sunday  Monday  Tuesday  Wednesday  Thursday  Friday  Saturday
5am       19      18       16         16        16      18        17
6am        0       0        1          0         0       0         1
7am       15      14       14         14        14      14        14
8am        0       0        0          0         1       0         0
9am        6       6        5          4         4       6         5
10am       0       0        1          0         0       0         1
11am      12      12       13         14        13      12        12
12am       0       0        0          1         0       1         0
1pm        6       6        4          4         5       6         5
2pm        0       0        1          0         0       0         1
3pm       18      18       17         16        17      17        17
4pm        0       0        1          0         1       0         0
5pm        6       6        5          5         4       6         5
6pm        0       0        1          0         1       0         1
7pm       12      12       13         14        13      13        12
8pm        0       0        0          0         1       0         1
9pm       18      18       16         16        17      18        17
10pm       0       0        1          0         0       0         1
11pm      16      16       16         15        16      15        15
12pm       0       0        0          0         1       0         0
1am        6       6        6          3         6       4         5
2am        0       0        0          0         0       0         0
3am       13      12       12         13        12      13        12
4am        0       0        0          0         1       0         1