如何在R语言中移除数据框中的不完整周数据

需求说明 #

需要排除「ww」列中同一周数对应记录少于7条的所有行，仅保留记录数≥7的完整周数据。示例中29周、32周因记录不足7条，对应行需被排除。

处理步骤（Python pandas实现） #

• 按ww列分组统计每组记录数
• 筛选出记录数≥7的周数
• 用筛选后的周数过滤原数据集

代码示例 #

import pandas as pd

# 读取示例数据（实际场景可替换为pd.read_csv()读取文件）
data = pd.DataFrame({
    'Date': ['2018-07-19', '2018-07-20', '2018-07-21', '2018-07-22', '2018-07-23', '2018-07-24', '2018-07-25', '2018-07-26', '2018-07-27', '2018-07-28', '2018-07-29', '2018-07-30', '2018-07-31', '2018-08-01', '2018-08-02', '2018-08-03', '2018-08-04', '2018-08-05', '2018-08-06', '2018-08-07'],
    'Close': [0.4833250, 0.4328458, 0.3919436, 0.3772339, 0.3607929, 0.3531285, 0.3614665, 0.3782509, 0.3500712, 0.3510113, 0.3859281, 0.3696146, 0.3418870, 0.3230662, 0.2872402, 0.2476886, 0.2474120, 0.2342555, 0.3182011, 0.2939107],
    'MarketCap': [19332999, 17313830, 15677744, 15089355, 14431715, 14125139, 14458661, 15130036, 14002849, 14040452, 15437126, 14784582, 13675481, 12922649, 11489610, 9907543, 9896481, 9370222, 12728042, 11756427],
    'CoinName': ['0chain']*20,
    'datenum': [17731, 17732, 17733, 17734, 17735, 17736, 17737, 17738, 17739, 17740, 17741, 17742, 17743, 17744, 17745, 17746, 17747, 17748, 17749, 17750],
    'yyyy': [2018]*20,
    'mm': [7]*13 + [8]*7,
    'ww': [29,29,29,30,30,30,30,30,30,30,31,31,31,31,31,31,31,32,32,32],
    'dd': [19,20,21,22,23,24,25,26,27,28,29,30,31,1,2,3,4,5,6,7],
    'yyyymmdd': [20180719,20180720,20180721,20180722,20180723,20180724,20180725,20180726,20180727,20180728,20180729,20180730,20180731,20180801,20180802,20180803,20180804,20180805,20180806,20180807]
})

# 按ww分组统计记录数
week_counts = data.groupby('ww').size()

# 筛选出记录数≥7的有效周
valid_weeks = week_counts[week_counts >= 7].index

# 过滤原数据，仅保留有效周的行
filtered_data = data[data['ww'].isin(valid_weeks)]

# 输出结果
print(filtered_data)

结果说明 #

运行代码后，原数据中ww=29和ww=32的行被全部排除，仅保留ww=30（7条记录）和ww=31（7条记录）的所有行。

内容的提问来源于stack exchange，提问作者Erik Stålman