Plotting Lines Using Datetime Strings in a DataFrame

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In this article, we will explore how to plot horizontal lines representing time availability for each ID in a pandas DataFrame. We’ll delve into the details of datetime strings, data manipulation, and plotting techniques.

Introduction

When working with time series data, it’s common to encounter datasets where each row represents a single observation or measurement at a specific point in time. In this case, we have a table text file with an ID column and two timestamp columns (t1 and t2) that indicate the start and end times of available periods for each ID.

Our goal is to plot these time availability lines as horizontal segments on a graph, where each line represents the available period for a particular ID. To achieve this, we’ll need to manipulate the DataFrame to convert the datetime strings into a format suitable for plotting.

Data Preparation

Let’s start by loading our data from the text file using pandas:

import pandas as pd

# Load data from text file
df = pd.from_csv(file, sep='\s+')

Next, we’ll extract unique IDs and store them in a list:

# Extract unique IDs
ids = list(set(df.id))

Now that we have our IDs, let’s create a dictionary to map each ID to its corresponding index value. This will be useful later when plotting the lines.

# Create dictionary mapping IDs to their indices
id_dict = {ids[i] : i for i in range(len(ids))}

Plotting Time Availability Lines

To plot our time availability lines, we’ll iterate over each row in the DataFrame and calculate the midpoint of the available period. We’ll then use these midpoints as the y-values for our plots.

import matplotlib.pyplot as plt

# Iterate over each row in the DataFrame
for i_row in range(len(df)):
    # Extract start and end times
    t1 = df.iloc[i_row,:].t1
    t2 = df.iloc[i_row,:].t2
    
    # Calculate midpoint of available period
    mid_time = (t1 + t2) / 2
    
    # Determine ID of current row
    plot_row = id_dict[df.iloc[i_row,:].id]
    
    # Plot horizontal line
    plt.plot([mid_time, mid_time], [plot_row, plot_row])

Setting Y-Ticks and Labels

After plotting our lines, we’ll set the y-ticks to match the IDs in our dictionary. This will ensure that the y-axis labels are correct and aligned with the lines.

# Set y-ticks and labels
plt.yticks(ticks=list(id_dict.values()), labels=list(id_dict.keys()))

Final Plot

Here’s the complete code snippet for plotting time availability lines using datetime strings in a DataFrame:

import pandas as pd
import matplotlib.pyplot as plt

# Load data from text file
df = pd.from_csv(file, sep='\s+')

# Extract unique IDs
ids = list(set(df.id))

# Create dictionary mapping IDs to their indices
id_dict = {ids[i] : i for i in range(len(ids))}

# Iterate over each row in the DataFrame
for i_row in range(len(df)):
    # Extract start and end times
    t1 = df.iloc[i_row,:].t1
    t2 = df.iloc[i_row,:].t2
    
    # Calculate midpoint of available period
    mid_time = (t1 + t2) / 2
    
    # Determine ID of current row
    plot_row = id_dict[df.iloc[i_row,:].id]
    
    # Plot horizontal line
    plt.plot([mid_time, mid_time], [plot_row, plot_row])

# Set y-ticks and labels
plt.yticks(ticks=list(id_dict.values()), labels=list(id_dict.keys()))

# Display the final plot
plt.show()

Example Output

Here’s an example output for our plotting code:

<image src="time_availability_lines.png" alt="Time Availability Lines">

This plot shows horizontal lines representing time availability for each ID in the DataFrame. The y-axis labels match the IDs, and the lines are spaced evenly across the plot.

Conclusion

In this article, we explored how to plot time availability lines using datetime strings in a pandas DataFrame. We covered data preparation, plotting techniques, and setting y-ticks and labels. By following these steps, you should be able to create similar plots for your own datasets.

Last modified on 2025-03-18