Python 3 解法, 执行用时: 772ms, 内存消耗: 524288KB, 提交时间: 2022-07-15

import pandas as pd
nowcoder = pd.read_csv('nowcoder.csv', parse_dates=True, index_col='date')
print(nowcoder.groupby(by='date')['question_id'].count())

Python 3 解法, 执行用时: 774ms, 内存消耗: 524288KB, 提交时间: 2022-07-17

import pandas as pd

fileData = pd.read_csv('nowcoder.csv', parse_dates=True, index_col='date')
fileData.index = fileData.index.map(lambda x: x.strftime('%Y-%m-%d'))
date_group = fileData.groupby('date')['question_id'].count()
print(date_group)

Python 3 解法, 执行用时: 779ms, 内存消耗: 524288KB, 提交时间: 2022-07-02

import pandas as pd
nowcoder = pd.read_csv('nowcoder.csv', parse_dates=True, index_col='date')
date_df = nowcoder.groupby('date')
print(date_df.size())

Python 3 解法, 执行用时: 780ms, 内存消耗: 524288KB, 提交时间: 2022-06-27

import pandas as pd
from datetime import date, datetime
nowcoder = pd.read_csv('nowcoder.csv', parse_dates=True, index_col='date')
#nowcoder['day']=nowcoder['date'].strftime('%Y-%m-%d')
print(nowcoder.groupby('date')['question_id'].count())

Python 3 解法, 执行用时: 784ms, 内存消耗: 524288KB, 提交时间: 2022-07-27

import pandas as pd
nowcoder = pd.read_csv('nowcoder.csv', parse_dates=True, index_col='date')

print(nowcoder.groupby('date').size())