how can i plot multiple graph into one with matplotlib or seaborn

Question

This is what my dataframe looks like: click on the line to download dataframe

enter link description here for dataframe

I have tried the following code :

plt.plot(LessDF['DeptAvg'][LessDF['classes'] == 'COA111'], LessDF['week1'])
plt.plot(LessDF['DeptAvg'][LessDF['classes'] == 'COA111'], LessDF['week2'])
plt.plot(LessDF['DeptAvg'][LessDF['classes'] == 'COA111'], LessDF['week3'])

I got the output below, which shows only one line, with my code.

I want output with separate lines, like this:

How can I get this output with matplotlib or seaborn??

Does this answer your question? [How to plot multiple dataframes in subplots](https://stackoverflow.com/questions/22483588/how-to-plot-multiple-dataframes-in-subplots) — T C Molenaar, Jan 20 '23 at 10:44
No this can't helpful to me @T C Molenaar your suggested solution is for subplot on same cell. I want multiple plot on one subplot. — Dipam Soni, Jan 20 '23 at 10:48
You should provide an example of your data to make your issue reproducible. It is not clear what `LessDF` looks like. It might be that your lines are just overlapping. https://stackoverflow.com/help/minimal-reproducible-example — Claudio Paladini, Jan 20 '23 at 10:57
I have updated the question & now can view the dataframe also. — Dipam Soni, Jan 20 '23 at 11:00

Claudio Paladini · Answer 1 · 2023-01-20T11:42:45.887

1

All your values in the DeptAvg column are 67 for the filter you applied.

Also, you are providing a boolean as your x: LessDF['DeptAvg'] == 'COA111'.

Also, you are applying the condition on the wrong column DeptAvg instead of classes

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

df = pd.read_csv('../../../Desktop/LessDF.csv')
df_filtered = df[df['classes'] == 'COA111' ]

plt.plot(df_filtered['week1'],df_filtered['DeptAvg'],alpha=.5,)
plt.plot(df_filtered['week2'],df_filtered['DeptAvg'],alpha=.5)
plt.plot(df_filtered['week3'],df_filtered['DeptAvg'],alpha=.5)

plt.legend(['week1','week2','week3'])

plt.show()

more info here

edited Jan 20 '23 at 11:42

answered Jan 20 '23 at 10:52

Claudio Paladini

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what are you talking about? the answer is given.. – Claudio Paladini Jan 20 '23 at 11:44
My intention was not to you @Claudio Paladini – Dipam Soni Jan 20 '23 at 11:52
This solution is helpful to me @Claudio Paladini. Thanks – Dipam Soni Jan 20 '23 at 11:54

ryu1kn · Accepted Answer · 2023-01-22T09:09:33.423

With Seaborn, with its object interface available from v0.12, you might do like this:

import pandas as pd
import seaborn as sns
import seaborn.objects as so

sns.set_theme()

First, convert the data frame into a long-form for easier processing in the second figure.

df = pd.read_csv("LessDF.csv", index_col=0)

df_long = (
    # Convert to a long-form
    pd.melt(df,
        id_vars=["Id", "classes", "LessAvg", "DeptAvg"],
        var_name=["week"],
        value_name="point"
    )

    # Make `week1` to `1`
    .assign(week=lambda df_: df_.week.str.replace("week", ""))
)

Then

(
    so.Plot(
        # We don't have to drop rows but since `DeptAvg` doesn't change
        # over `classes` and `week`, we can de-duplicate them
        df_long.drop_duplicates(["classes", "week"]),
        x="week", y="DeptAvg", color="classes"
    )
    .add(so.Line())
    .limit(y=(0, 100))
)

If you'd like to also render the individual Id's point of each week, you might do something like this:

(
    so.Plot(data=df_long, x="week", y="point", color="classes")
    .add(so.Dots(), so.Dodge(), so.Jitter(.3))
    .add(so.Line(linewidth=3, alpha=.8), y="DeptAvg")
    .limit(y=(0, 100))
)

This is the exact solution i wated @ryu 1 kn Thanks. This will helps me to solve my many of doubts. — Dipam Soni, Jan 22 '23 at 06:24

score 0 · Answer 3 · answered Jan 20 '23 at 11:55

# I done this using seaborn you can use matplotlib in between to code
plt.figure(figsize=(16, 16)) 
plt.subplot(no_of_rows, no_of_columns, plot_num)
plt.title('Any title 1')
sns.boxplot(df['column_name'])

Example :- we want 2 rows with columns of plots then we use
plt.subplot(2, 2, 1)
plt.title('Any title 1')
sns.distplot(df['column_name'], bins=20)

plt.subplot(2, 2, 2)
plt.title('Any title 2')
sns.distplot(df['column_name'], bins=20)

plt.subplot(2, 2, 3)
plt.title('Any title 3')
sns.distplot(df['column_name'], bins=20)

plt.subplot(2, 2, 4)
plt.title('Any title 4')
sns.distplot(df['column_name'], bins=20)

plt.show()

as per the comments to the questions, he is not looking for subplots. Instead, he is looking for multiple lines in one plot. — Claudio Paladini, Jan 20 '23 at 17:57

score 0 · Answer 4 · answered Jan 21 '23 at 05:18

fig, ax = plt.subplots(2,3, figsize=(16,10))

sns.boxplot(df,y="arpu_6",ax=ax[0,0])
ax[0,0].set_title("June ARPU")
ax[0,0].set_ylim([0, 5000])

sns.boxplot(df,y="arpu_7",ax=ax[0,1])
ax[0,1].set_title("July ARPU")
ax[0,1].set_ylim([0, 5000])

sns.boxplot(df,y="arpu_8",ax=ax[0,2])
ax[0,2].set_title("Aug ARPU")
ax[0,2].set_ylim([0, 5000])

I picked off the code from my own notebook, so doesn't match your dataframe, so just modify as per your needs.

how can i plot multiple graph into one with matplotlib or seaborn

4 Answers4