提问人：Rabia Sönmez 提问时间：9/9/2023 最后编辑：Rabia Sönmez 更新时间：9/9/2023 访问量：28
如何在 gnuplot 或 python 中进行数据分箱？
How to do data binning in gnuplot or python?
问：
我正在尝试在 python 中进行数据分箱。我想得到的图表是original_graph。但我越来越my_plot。我想将数据装箱为纬度 2 度范围和海拔 100 公里范围。等待您的帮助，我的代码如下;
import csv
import numpy as np
import matplotlib.pyplot as plt
csv_file = 'new.csv'
latitude_data = []
altitude_data = []
color_data = []
with open(csv_file, 'r', encoding='utf-8-sig') as file:
csvreader = csv.reader(file)
for row in csvreader:
latitude = float(row[2]) # Third column (latitude)
altitude = float(row[1]) # Second column (altitude)
color_value = float(row[0]) # First column
latitude_data.append(latitude)
altitude_data.append(altitude)
color_data.append(color_value)
latitude_bin_width = 2.0 # Two-degree range in latitude
altitude_bin_width = 100 # 100-kilometer range in altitude
num_latitude_bins = int((max(latitude_data) - min(latitude_data)) / latitude_bin_width) + 1
num_altitude_bins = int((max(altitude_data) - min(altitude_data)) / altitude_bin_width) + 1
H, xedges, yedges = np.histogram2d(latitude_data, altitude_data, bins=[num_latitude_bins, num_altitude_bins])
plt.figure(figsize=(12, 8))
plt.scatter(latitude_data, altitude_data, c=color_data, cmap='jet', marker='o', alpha=0.5, s=100)
plt.colorbar(label='First Column Value', format='%.0e')
plt.show()
答：
0赞
Marco Parola
9/9/2023
#1
您似乎想要创建具有纬度和高度特定图格宽度的 2D 直方图，然后根据您的数据创建带有颜色编码的散点图。您的代码差不多就在那里，但您需要使用 np.histogram2d 函数来计算直方图，然后使用 imshow：
import csv
import numpy as np
import matplotlib.pyplot as plt
csv_file = 'new.csv'
latitude_data = []
altitude_data = []
color_data = []
with open(csv_file, 'r', encoding='utf-8-sig') as file:
csvreader = csv.reader(file)
for row in csvreader:
latitude = float(row[2]) # Third column (latitude)
altitude = float(row[1]) # Second column (altitude)
color_value = float(row[0]) # First column
latitude_data.append(latitude)
altitude_data.append(altitude)
color_data.append(color_value)
latitude_bin_width = 2.0 # Two-degree range in latitude
altitude_bin_width = 100 # 100-kilometer range in altitude
num_latitude_bins = int((max(latitude_data) - min(latitude_data)) / latitude_bin_width) + 1
num_altitude_bins = int((max(altitude_data) - min(altitude_data)) / altitude_bin_width) + 1
H, xedges, yedges = np.histogram2d(latitude_data, altitude_data, bins=[num_latitude_bins, num_altitude_bins])
# Create a 2D histogram plot
plt.figure(figsize=(12, 8))
plt.imshow(H.T, origin='lower', extent=[min(latitude_data), max(latitude_data), min(altitude_data), max(altitude_data)],
cmap='jet', aspect='auto', interpolation='none')
plt.colorbar(label='Frequency')
# Scatter plot your original data points
plt.scatter(latitude_data, altitude_data, c=color_data, cmap='jet', marker='o', alpha=0.5, s=100)
plt.xlabel('Latitude')
plt.ylabel('Altitude (km)')
plt.title('Scatter Plot with 2D Histogram')
plt.show()
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