您可以使用groupby()-〉transform()来处理按每个人分组的记录块。按日期对记录进行排序，并检查前一个日期的状态是否为“是”。收集所有带有肯定检查标志的结果。
在每行之前添加注解以解释逻辑。

# For each "Name", check if previous date has status "Yes".
def check_prev_date_status(g):
    df_g = g.apply(pd.Series)

    # Sort by date.
    df_g = df_g.sort_values(0)

    # Check if last but one status is "Yes".
    if df_g[-2:-1][1].values[0] == "Yes":
      return 1
    else:
      return 0

# Compute tuple of "Date" and "Status" for easy processing as one column. It is hard to process multiple columns with "transform()".
df["Date_Status"] = df[["Date", "Status"]].apply(tuple, axis=1)

# Apply above function and compute flag if previous date has status "Yes".
df["check_status_flag"] = df.groupby("Name")[["Date_Status"]].transform(check_prev_date_status)

# Filter and count the results.
print(df[df["check_status_flag"] == 1]["Name"].unique())

输出：

['John' 'Emily']