1D Multiple Lines Plot With Pandas

I have a dataframe with x1 and x2 columns. I want to plot each row as an unidimensional line where x1 is the start and x2 is the end. Follows I have my solution which is not very c

Solution 1:

You can use DataFrame.apply with axis=1 for process by rows:

def plot(dataframe):
    plt.figure()
    dataframe.apply(lambda x: plt.hlines(0,x['x1'],x['x2']), axis=1)

plot(df_lines)

Solution 2:

Matplotlib can save a lot of time drawing lines, when they are organized in a LineCollection. Instead of drawing 50 individual hlines, like the other answers do, you create one single object.

Such a LineCollection requires an array of the line vertices as input, it needs to be of shape (number of lines, points per line, 2). So in this case (50,2,2).

import numpy as np
import pandas as pd    
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection

df_lines = pd.DataFrame({'x1': np.linspace(1,50,50)*2, 
                         'x2': np.linspace(1,50,50)*2+1})

segs = np.zeros((len(df_lines), 2,2))
segs[:,:,0] = df_lines[["x1","x2"]].values


fig, ax = plt.subplots()

line_segments = LineCollection(segs)
ax.add_collection(line_segments)

ax.set_xlim(0,102)
ax.set_ylim(-1,1)
plt.show()

Solution 3:

I add to the nice @jezrael response the possibility to do this in the numpy framework using numpy.apply_along_axis. Performance-wise it is equivalent to DataFrame.apply:

def plot(dataframe):
    plt.figure()
    np.apply_along_axis(lambda x: plt.hlines(0,x[0],x[1]), 1,dataframe.values)
    plt.show()

plot(df_lines)