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I have a dataframe of XY coordinates which I'm plotting as Markers in a Scatter plot. I'd like to add_trace lines between specific XY pairs, not between every pair. For example, I'd like a line between Index 0 and Index 3 and another between Index 1 and Index 2. This means that just using a line plot won't work as I don't want to show all the connections. Is it possible to do it with a version of iloc or do I need to make my DataFrame in 'Wide-format' and have each XY pair as separate column pairs? I've read through this but I'm not sure it helps in my case. Adding specific lines to a Plotly Scatter3d() plot

enter image description here

import pandas as pd
import plotly.graph_objects as go

# sample data
d={'MeanE': {0: 22.448461538460553, 1: 34.78435897435799, 2: 25.94307692307667, 3: 51.688974358974164},
   'MeanN': {0: 110.71128205129256, 1: 107.71666666666428, 2: 140.6384615384711, 3: 134.58615384616363}}

# pandas dataframe
df=pd.DataFrame(d)

# set up plotly figure
fig = go.Figure()

fig.add_trace(go.Scatter(x=df['MeanE'],y=df['MeanN'],mode='markers')) 
       
fig.show()

enter image description here

UPDATE: Adding the accepted answer below to what I had already, I now get the following finished plot. enter image description here

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1 Answer 1

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  • taken approach of updating data frame rows that are the pairs of co-ordinates where you have defined
  • then add traces to figure to complete requirement as a list comprehension
import pandas as pd
import plotly.graph_objects as go

# sample data
d={'MeanE': {0: 22.448461538460553, 1: 34.78435897435799, 2: 25.94307692307667, 3: 51.688974358974164},
   'MeanN': {0: 110.71128205129256, 1: 107.71666666666428, 2: 140.6384615384711, 3: 134.58615384616363}}

# pandas dataframe
df=pd.DataFrame(d)

# set up plotly figure
fig = go.Figure()

fig.add_trace(go.Scatter(x=df['MeanE'],y=df['MeanN'],mode='markers')) 

# mark of pairs that will be lines
df.loc[[0, 3], "group"] = 1
df.loc[[1, 2], "group"] = 2
# add the lines to the figure
fig.add_traces(
    [
        go.Scatter(
            x=df.loc[df["group"].eq(g), "MeanE"],
            y=df.loc[df["group"].eq(g), "MeanN"],
            mode="lines",
        )
        for g in df["group"].unique()
    ]
)

fig.show()

enter image description here

alternate solution to enhanced requirement in comments

# mark of pairs that will be lines
lines = [[0, 3], [1, 2], [0,2],[1,3]]
# add the lines to the figure
fig.add_traces(
    [
        go.Scatter(
            x=df.loc[pair, "MeanE"],
            y=df.loc[pair, "MeanN"],
            mode="lines",
        )
        for pair in lines
    ]
)
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6 Comments

That works. If I want to link more, how do I do that? I naively tried this but I only get the last two lines plotted. df.loc[[0, 3], "group"] = 1 df.loc[[1, 2], "group"] = 2 df.loc[[0, 2], "group"] = 3 df.loc[[1, 3], "group"] = 4
your group 3 & 4 use same rows as 1&2 therefore the information on which lines to plot is overwritten. Is your question really you have an list of pairs of rows you want to plot lines for?
I've provided a very similar alternate solution for pairs of rows defined in a list
much appreciated. For this project I am just looking at specific combinations or pairs (I have other projects where I might want to plot all pairs). I've edited my question with the finished plot using your code. I wanted to visualise the diagonal distances between the Mean of a scatter of points.
you need to switch to looping rather than a list comprehension and use add_trace() instead of add_traces()
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