读取iris数据集中鸢尾花的萼片、花瓣长度数据（见iris.csv）,并对其进行排序、去重、并求出和、累积和、均值、标准差、方差、最小值、最大值。python

首先，你需要导入必要的库，如pandas用于数据处理，numpy用于数学计算，以及matplotlib进行数据可视化。假设iris.csv文件已经存在，并且列名分别为"sepal_length", "petal_length"。以下是相应的步骤：

import pandas as pd
import numpy as np

# 1. 读取数据
df_iris = pd.read_csv('iris.csv')

# 2. 数据清洗和预处理
# 排序
sorted_df = df_iris.sort_values(by=['sepal_length', 'petal_length'])

# 去重（如果有多余行）
unique_df = sorted_df.drop_duplicates()

# 求和
sums = unique_df[['sepal_length', 'petal_length']].sum()

# 累积和
cumulative_sums = unique_df[['sepal_length', 'petal_length']].cumsum()

# 计算统计量
mean = unique_df[['sepal_length', 'petal_length']].mean()
std_dev = unique_df[['sepal_length', 'petal_length']].std()
variance = unique_df[['sepal_length', 'petal_length']].var()
min_values = unique_df[['sepal_length', 'petal_length']].min()
max_values = unique_df[['sepal_length', 'petal_length']].max()

# 输出结果
print("Summary statistics:")
print(f"Sum of sepal lengths: {sums['sepal_length']}")
print(f"Sum of petal lengths: {sums['petal_length']}")

print("\nCumulative sums:")
print(cumulative_sums)

print("\nMean values:")
print(mean)

print("\nStandard deviation:")
print(std_dev)

print("\nVariance:")
print(variance)

print("\nMinimum values:")
print(min_values)

print("\nMaximum values:")
print(max_values)