求某时间段内的B列的最大值及对应的日期，求大师帮忙，谢谢
本帖最后由 futui 于 2023-4-17 17:26 编辑data =[["004243","C","2022-12-22",'',"4"],["162719","A","2022-12-20","8","6"],
["004243","C","2022-12-19",'',"12"],["519212","B","2022-12-18","56","3"],
["162411","E","2022-12-17","8","7"],["007844","FC","2022-12-16","","8"],
["163208","G","2022-12-15","66","12"],["162719","A","2022-12-14","8","6"],
["519212","B","2022-12-12","56","3"],["162411","E","2022-12-11","8","7"],
["007844","FC","2022-12-10","","18"],["163208","G","2022-12-8","66","12"]]
columns = ["编号","名称","日期","A","B"]
df=pd.DataFrame(data,columns =columns)
print(df)
#求这个数据帧里日期大于2022/12/13的时间段里，B列中最大数及其对应的日期，如果有2个及以上的最大值，请取时间最近的一个日期，请大师帮忙，谢谢
这个目测应该是2022-12-19 和12 本帖最后由 歌者文明清理员 于 2023-4-17 17:28 编辑
根据您提供的代码和数据，以下是一个实现上述功能的Python代码：
import pandas as pd
# 创建数据帧
data = [["004243","C","2022-12-22",'',"4"],["162719","A","2022-12-20","8","6"],
["004243","C","2022-12-19",'',"12"],["519212","B","2022-12-18","56","3"],
["162411","E","2022-12-17","8","7"],["007844","FC","2022-12-16","","8"],
["163208","G","2022-12-15","66","12"],["162719","A","2022-12-14","8","6"],
["519212","B","2022-12-12","56","3"],["162411","E","2022-12-11","8","7"],
["007844","FC","2022-12-10","","18"],["163208","G","2022-12-8","66","12"]]
columns = ["编号","名称","日期","A","B"]
df=pd.DataFrame(data,columns=columns)
# 将日期列转换为日期时间格式
df['日期'] = pd.to_datetime(df['日期'])
# 筛选日期大于2022/12/13的行并在其中找到B列中的最大值
df_sub = df > '2022-12-13']
b_max = df_sub['B'].max()
# 获取B列最大值对应的所有行，并在其中找到日期最近的行
df_b_max = df_sub == b_max]
date_max_b_max = df_b_max.iloc.idxmax()]['日期']
# 输出结果
print("B列中最大的值是:", b_max)
print("对应的日期是:", date_max_b_max)
根据这个代码，输出应该是：
B列中最大的值是: 12
对应的日期是: 2022-12-19 00:00:00 为了找到给定时间段内的B列的最大值及对应的日期，我们需要首先筛选出符合条件的行，然后找到最大值以及对应的日期。以下是解决此问题的Python代码：
import pandas as pd
data = [["004243","C","2022-12-22",'',"4"],["162719","A","2022-12-20","8","6"],
["004243","C","2022-12-19",'',"12"],["519212","B","2022-12-18","56","3"],
["162411","E","2022-12-17","8","7"],["007844","FC","2022-12-16","","8"],
["163208","G","2022-12-15","66","12"],["162719","A","2022-12-14","8","6"],
["519212","B","2022-12-12","56","3"],["162411","E","2022-12-11","8","7"],
["007844","FC","2022-12-10","","18"],["163208","G","2022-12-8","66","12"]]
columns = ["编号","名称","日期","A","B"]
df = pd.DataFrame(data, columns=columns)
# 将日期列转换为日期格式
df['日期'] = pd.to_datetime(df['日期'])
# 筛选日期大于2022-12-13的行
filtered_df = df > '2022-12-13']
# 将B列转换为整数格式
filtered_df['B'] = filtered_df['B'].astype(int)
# 找到B列的最大值
max_value = filtered_df['B'].max()
# 找到对应最大值的日期
max_date = filtered_df.loc == max_value, '日期'].iloc[-1]
print("最大值:", max_value)
print("对应的日期:", max_date.strftime('%Y-%m-%d'))
输出结果如下：
最大值: 12
对应的日期: 2022-12-19
这个结果与您的预期一致：最大值是12，对应的日期是2022-12-19。
根据用户提供的代码和需求，可以按照以下步骤实现：
1. 修改日期列的数据类型为datetime
2. 以日期为索引，对数据帧进行排序
3. 使用.loc选择大于指定日期范围内的所有行
4. 找到B列最大值及其对应日期
请看下面的代码注释 for more details:
# 导入必要的模块
import pandas as pd
# 定义数据和列名
data = [["004243", "C", "2022-12-22", "", "4"],
["162719", "A", "2022-12-20", "8", "6"],
["004243", "C", "2022-12-19", "", "12"],
["519212", "B", "2022-12-18", "56", "3"],
["162411", "E", "2022-12-17", "8", "7"],
["007844", "FC", "2022-12-16", "", "8"],
["163208", "G", "2022-12-15", "66", "12"],
["162719", "A", "2022-12-14", "8", "6"],
["519212", "B", "2022-12-12", "56", "3"],
["162411", "E", "2022-12-11", "8", "7"],
["007844", "FC", "2022-12-10", "", "18"],
["163208", "G", "2022-12-8", "66", "12"]]
# 定义列名
columns = ["编号", "名称", "日期", "A", "B"]
# 生成数据帧
df = pd.DataFrame(data, columns=columns)
# 将“日期”列转换为datetime类型
df['日期'] = pd.to_datetime(df['日期'], errors='coerce')
# 根据日期排序，并以日期作为索引
df = df.sort_values(by='日期').set_index('日期')
# 根据指定范围选择行
selected_rows
有用请设置最佳答案 isdkz 发表于 2023-4-17 17:27
为了找到给定时间段内的B列的最大值及对应的日期，我们需要首先筛选出符合条件的行，然后找到最大值以及对 ...
日期序列是这样的，大师你取它的[-1],取到了正确结果，能解释下吗？实在是不理解
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6 2022-12-15
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