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

# 1st DataFrame
data1 = {
'X': range(10),
'Y': [x**2 for x in random.sample(range(1, 100), 10)],
'Z': [x*2 for x in random.sample(range(1, 100), 10)]
}
df1 = pd.DataFrame(data1)

# 2nd DataFrame
data2 = {
'X': range(10),
'Y': [x**2 for x in random.sample(range(1, 100), 10)],
'Z': [x*2 for x in random.sample(range(1, 100), 10)]
}
df2 = pd.DataFrame(data2)

# 3rd DataFrame
data3 = {
'X': range(10),
'Y': [x**2 for x in random.sample(range(1, 100), 10)],
'Z': [x*2 for x in random.sample(range(1, 100), 10)]
}
df3 = pd.DataFrame(data3)

# Plot and save 1st df using pandas plot
start = time.time()
ax1 = df1.plot(x='X', y=['Y', 'Z'], figsize=(8, 6), marker='o', title='DataFrame 1 Plot')
ax1.set_xlabel('X')
ax1.set_ylabel('Values')
ax1.grid(True)
plt.savefig('dataframe1_plot.png')
plt.close()
end = time.time()
print(f"Time for plot 1: {end - start:.2f} seconds")

# Plot and save 2nd df using pandas plot
start = time.time()
ax2 = df2.plot(x='X', y=['Y', 'Z'], figsize=(8, 6), marker='o', title='DataFrame 2 Plot')
ax2.set_xlabel('X')
ax2.set_ylabel('Values')
ax2.grid(True)
plt.savefig('dataframe2_plot.png')
plt.close()
end = time.time()
print(f"Time for plot 2: {end - start:.2f} seconds")

# Plot and save 3rd df using pandas plot
start = time.time()
ax3 = df3.plot(x='X', y=['Y', 'Z'], figsize=(8, 6), marker='o', title='DataFrame 3 Plot')
ax3.set_xlabel('X')
ax3.set_ylabel('Values')
ax3.grid(True)
plt.savefig('dataframe3_plot.png')
plt.close()
end = time.time()
print(f"Time for plot 3: {end - start:.2f} seconds")

Time for plot 1: 134.06 seconds
Time for plot 2: 0.29 seconds
Time for plot 3: 0.23 seconds

Warum läuft der erste von Matplotlib oder pandas df.plot verarbeitete Plot im Vergleich zu allen nachfolgenden Plots extrem langsam? Dies tritt sogar dann auf, wenn die nachfolgenden Diagramme völlig unterschiedliche Variablen verwenden. Gibt es eine Lösung, um die Geschwindigkeit des ersten Plots zu erhöhen?
Ein Beispiel:
[code]import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import time
import random

# 1st DataFrame
data1 = {
'X': range(10),
'Y': [x**2 for x in random.sample(range(1, 100), 10)],
'Z': [x*2 for x in random.sample(range(1, 100), 10)]
}
df1 = pd.DataFrame(data1)

# 2nd DataFrame
data2 = {
'X': range(10),
'Y': [x**2 for x in random.sample(range(1, 100), 10)],
'Z': [x*2 for x in random.sample(range(1, 100), 10)]
}
df2 = pd.DataFrame(data2)

# 3rd DataFrame
data3 = {
'X': range(10),
'Y': [x**2 for x in random.sample(range(1, 100), 10)],
'Z': [x*2 for x in random.sample(range(1, 100), 10)]
}
df3 = pd.DataFrame(data3)

# Plot and save 1st df using pandas plot
start = time.time()
ax1 = df1.plot(x='X', y=['Y', 'Z'], figsize=(8, 6), marker='o', title='DataFrame 1 Plot')
ax1.set_xlabel('X')
ax1.set_ylabel('Values')
ax1.grid(True)
plt.savefig('dataframe1_plot.png')
plt.close()
end = time.time()
print(f"Time for plot 1: {end - start:.2f} seconds")

# Plot and save 2nd df using pandas plot
start = time.time()
ax2 = df2.plot(x='X', y=['Y', 'Z'], figsize=(8, 6), marker='o', title='DataFrame 2 Plot')
ax2.set_xlabel('X')
ax2.set_ylabel('Values')
ax2.grid(True)
plt.savefig('dataframe2_plot.png')
plt.close()
end = time.time()
print(f"Time for plot 2: {end - start:.2f} seconds")

# Plot and save 3rd df using pandas plot
start = time.time()
ax3 = df3.plot(x='X', y=['Y', 'Z'], figsize=(8, 6), marker='o', title='DataFrame 3 Plot')
ax3.set_xlabel('X')
ax3.set_ylabel('Values')
ax3.grid(True)
plt.savefig('dataframe3_plot.png')
plt.close()
end = time.time()
print(f"Time for plot 3: {end - start:.2f} seconds")
[/code]
Wenn ich mir die time.time-Ergebnisse ansehe, erhalte ich immer etwas, das so aussieht:
[code]Time for plot 1: 134.06 seconds
Time for plot 2: 0.29 seconds
Time for plot 3: 0.23 seconds
[/code]