plotly-signif 0.0.41

A python class of drawing a Bar/Box plot based on the plotly package, with freely definable statistical annotations

plotly-signif

A python class of drawing a Bar/Box plot based on the plotly package, with freely definable statistical annotations

How to use

Download

• Use pip

pip install plotly-signif

You can import like this:

from plotly_signif import plotly_signif
# or
from plotly_signif import *

• Download the plotly_signif.py to the path of your program

  from plotly_signif import *

• Enjoy it

Bar

You can refer to the following example :

from plotly_signif import *
import pandas as pd
iris = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv')
df1 = iris.groupby("species").mean()
df2 = iris.groupby("species").sem()

test = plotly_signif(data=df1,error=df2,text={"x":"X","y":"Y"})  
test.plot()
# 添加统计注释
annotation_list = [[0,1,1],[2,0,3,-1],[2,1,2,2],[0,1,3,6],[0,2,3,9]]
test.add_annotations(annotation_list = annotation_list,text="***",inne_color="#B799FF")   
test.add_annotations(annotation_list = [[1,2,3,3]],text="🏅",sign_d_index=2) 
test.add_annotations(annotation_list = [[1,1,2,4]],text="😭",sign_d_index=2) 
test.add_annotations(annotation_list = [[1,0,2,2]],text="⭐⭐⭐",sign_d_index=2,size=12) 
test.add_annotations(annotation_list = [[1,2,0]],text="ns",size=14,sign_d_index=2.5) 
# 绘制/保存
test.show("./image/example.png")  # 保存使用属性 save_path = "./image/example.png" 

test2 = plotly_signif(data=df1,error=df2,text={"x":"X","y":"Y"})  
test2.set_color(["#453C67","#6D67E4",'#B799FF','#ACBCFF']) # change the colors
test2.plot(pic_px=[580,650])
# An example of changing labels based on plotly syntax
test2.fig.update_layout(
    title = dict(  # set the title
        text = "Test 2",
        font = {'size': 20},
        x = 0.5,
        y = 0.9,
        ),
)
test2.fig.update_layout(   # set the side labels
                legend=dict(
                    orientation="h",
                    x=0.12,
                    y=-0.15, 
                    traceorder="normal",
                    font=dict(size=16),
                ),
            )
test2.add_annotations(annotation_list = [[0,1,3,6]],text="🧠",sign_d_index=2) 
test2.add_annotations(annotation_list = [[0,0,3,3]],text="❓",sign_d_index=2) 
test2.add_annotations(annotation_list = [[1,0,0,2.3]],text="👽",sign_d_index=2,inne_color="#FFFFFF") 
test2.add_annotations(annotation_list = [[1,2,2,5]],text="🤖",sign_d_index=2,inne_color="#FFFFFF") 
test2.add_annotations(annotation_list = [[1,1,1,7.6]],text="🐵",sign_d_index=2,inne_color="#FFFFFF") 
test2.add_annotations(annotation_list = [[1,3,3,10]],text="🐁",sign_d_index=2,inne_color="#FFFFFF") 
test2.show()

Box

data = pd.read_csv('https://raw.githubusercontent.com/mwaskom/seaborn-data/master/fmri.csv')


    subject	timepoint	event	region	signal
0	s13	18	stim	parietal	-0.017552
1	s5	14	stim	parietal	-0.080883
2	s12	18	stim	parietal	-0.081033
3	s11	18	stim	parietal	-0.046134
4	s10	18	stim	parietal	-0.037970
...	...	...	...	...	...
1059	s0	8	cue	frontal	0.018165
1060	s13	7	cue	frontal	-0.029130
1061	s12	7	cue	frontal	-0.004939
1062	s11	7	cue	frontal	-0.025367
1063	s0	0	cue	parietal	-0.006899

Box_test = plotly_signif(data=data,text={"x":"Region","y":"Signal"},mode="Box")  
Box_test.plot(pic_px=[840,620],Box_list=["subject","region","signal"])
annotation_list = [[0,1,0],[0,0,2,1],[0,2,5,4],[1,3,4,5]]
Box_test.add_annotations(annotation_list=annotation_list)
Box_test.fig.update_layout(title_text="Seaborn-data-fmri groupby subject")
Box_test.show()

Parameter explanation

🌀 You can use plotly's syntax to set the object.fig , new settings will overwrite the default settings.

• __init__ :
  • data : Data frame used for drawing bar chart
  • error : Data frame corresponding to error bars, only used with mode = "Bar"
  • text : Image text label
  • mode : default = "Bar" , and supports "Box" to plot
• plot()
  • pic_px : image size list , [width,height] , The unit is px
  • Box_list : If a box plot is drawn, the meaning of this list is ["which Group","which x","which y"]
• add_annotations()

  • annotation_list : A two-dimensional list representing the position of the annotation, with each sublist representing an annotation. The length of 3 is the inter-group annotation, the length of 4 is the intra-group annotation, and the last value controls the y-axis position.

    [0,1,1] means that the annotation is between the 1/2th group, and the y-axis position drops 1 level relative to y_max; [2,0,3,-1] means that the annotation is within the 3rd group, and within the group In the 1/4th column, the y-axis position rises one level relative to y_max.

    表示注释在什么位置的二维列表，每一个子列表表示一个注释。长度为3的是组间注释，长度4为组内注释，最后一个值控制y轴位置。

    [0,1,1] 表示注释在第1/2个组之间，y轴位置相对于 y_max 下降1层；[2,0,3,-1] 表示注释在第3个组内，组内的第1/4个柱间，y轴位置相对于 y_max 上升一层。

  • text : annotation symbol, default = "***" , which can also be 🪙🆙🏅⭐🔥🍋💔😃😭 ... symbols, visible https://www.emojiall.com/zh-hans/copy

  • size : symbol font size, default = 16

  • line_width : line width, default = 1.5

  • color : intergroup annotation color, default = 'rgba(0,0,0,1)'

  • inne_color : annotation color within group, default = "rgba(100,100,100,1)"

  • y_max_index : The y-height of the annotation when layer is set to 0, default = 1.15 , multiply the height of the tallest bar in the chart by y_max_index to get y_max

  • layer_down_index : control the spacing between upper and lower layers, default = 0.08 , layer_down = layer_down_index $ \times $ y_max

  • sign_d_index : distance between line and symbol, default = 4 , layer_down / sign_d_index

  • line_d_index : the length of the hanging line, default = 3.2 , layer_down / line_d_index

• show()
  • save_path : path to save.
• set_color() : set the color of the column, given a list set_color() need before use plot()

TODO

• Supports boxplots
• Supports horizontal drawing

requirement

• numpy
• pandas
• plotly
• kaleido (There may be problems with the installation of this package)

Any feedback on bugs or suggestions for features are welcome