分析pandas中多个.txt文件中的数据

import pandas as pd

file_paths = ['file1.txt', 'file2.txt', 'file3.txt']  # 替换为实际的文件路径
data_frames = []

for file_path in file_paths:
    df = pd.read_csv(file_path, delimiter='\t')  # 替换为实际的分隔符
    data_frames.append(df)

merged_df = pd.concat(data_frames)

merged_df.drop_duplicates(inplace=True)  # 去除重复值
merged_df.dropna(inplace=True)  # 去除缺失值
merged_df['column_name'] = merged_df['column_name'].astype(int)  # 将某一列的数据类型转换为整数

mean_value = merged_df['column_name'].mean()  # 计算某一列的均值
median_value = merged_df['column_name'].median()  # 计算某一列的中位数
std_value = merged_df['column_name'].std()  # 计算某一列的标准差

import matplotlib.pyplot as plt

merged_df['column_name'].plot(kind='hist')  # 绘制柱状图
plt.xlabel('Value')
plt.ylabel('Frequency')
plt.title('Histogram of column_name')
plt.show()