Python: plot panda dataframe of type series

Question

I have a dataframe (df) with 10 rows looking like this

-2.00    [-24.4907, -24.4594, -24.4321, -24.4012, -24.3...
-1.75    [-23.8154, -23.7849, -23.7601, -23.7326, -23.7...
-1.00    [-23.7131, -23.6954, -23.6767, -23.6616, -23.6...
-0.75    [-22.7675, -22.7505, -22.741, -22.7173, -22.70...
-0.50    [-22.0693, -22.0718, -22.0481, -22.0328, -22.0...
 0.50    [-15.8461, -15.8247, -15.7963, -15.7784, -15.7...
 1.00    [-7.32122, -7.27283, -7.2336, -7.19238, -7.153...
 1.25    [-3.44732, -3.37547, -3.30565, -3.23125, -3.15...
 1.75    [0.541327, 0.568081, 0.597821, 0.627494, 0.667...
 2.50    [3.63716, 3.68494, 3.73379, 3.77966, 3.82584, ...
dtype: object

I'm not 100% sure but I think it contains ndarrays, I'll give you the info that I have:

type(df)
pandas.core.series.Series

whos
df  Series  -2.00    [-24.4907, -24.4<...>82584, ...\ndtype: object

Anyway, I would like to plot all of these arrays in one plot. I'm able to plot one array using

plt.plot(df[1])

And since I have a dataframe of type "series" I hoped using

df.plot
plt.plot()

would be the solution but it doesn't plot anything. Do you know what I do wrong?

Assuming, your data is like what's pointed out in answer, try pd.DataFrame(df['values'].values.tolist(), index=df['id']).plot(subplots=True)? — Zero
– Zero, Commented Sep 18, 2017 at 17:35
@Zero the dataframe I have is a bit different than the one used in the example I think. And I'm not smart enough to transfer your idea to my dataframe. — Svenno Nito
– Svenno Nito, Commented Sep 19, 2017 at 10:38

Heapify · Accepted Answer · 2017-09-18 16:14:13Z

1

You have to run a for loop and call plt.plot() repeatedly with the data you want. When you come out of the for loop, say plt.show() and all of your plots should be added to the same figure. Here is what worked for me:

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

val_list = [np.array([1,2]), np.array([4,3])]
data = {"id": [1,2],
        "values": val_list
       }
df = pd.DataFrame(data)
for i in range(2):
    plt.plot(df.iloc[:, 0], df.iloc[i, 1])
    plt.plot(df.iloc[:, 0], df.iloc[i, 1])
plt.show()

The above code added both plots to my figure

answered Sep 18, 2017 at 16:14

Heapify

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1 Comment

Svenno Nito Over a year ago

Thanks for your idea! I always try to avoid for-loops though, do you think there's a way to plot it without a for-loop?

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