python-datetime

问题 I'd like to convert a dataframe column which has a date string. But in some cases, the date string might be empty due to certain conditions. So I just want all the other rows in that column to be converted to datetime format except the rows in that particular column which might be blank. Is it possible? What I've tried so far: Option1: df['etime'] = pd.to_datetime(df['etime'],errors='ignore').dt.strftime('%Y-%m-%d %H:%M') Option 2: for ind in df.index: if (df['etime'].str.len()[ind] == 0) :

问题 I have a dataframe which has a column of type Timestamp. I want to find the time elapsed (in seconds) since midnight as a new column. How to do it in a simple way ? Eg : Input : samples['time'] 2018-10-01 00:00:01.000000000 2018-10-01 00:00:12.000000000 type(samples['time'].iloc[0]) <class 'pandas._libs.tslib.Timestamp'> Output : samples['time_elapsed'] 1 12 回答1: Note that the date part in each row may be other (not from one and the same day), so you can not take any "base date" ( midnight )

问题 I have a dataframe which has a column of type Timestamp. I want to find the time elapsed (in seconds) since midnight as a new column. How to do it in a simple way ? Eg : Input : samples['time'] 2018-10-01 00:00:01.000000000 2018-10-01 00:00:12.000000000 type(samples['time'].iloc[0]) <class 'pandas._libs.tslib.Timestamp'> Output : samples['time_elapsed'] 1 12 回答1: Note that the date part in each row may be other (not from one and the same day), so you can not take any "base date" ( midnight )

问题 There are two Dataframes. First is like this: print df1 id date month is_buy 0 17 2015-01-16 2015-01 1 1 17 2015-01-26 2015-01 1 2 17 2015-01-27 2015-01 1 3 17 2015-02-11 2015-02 1 4 17 2015-03-14 2015-03 1 5 18 2015-01-28 2015-01 1 6 18 2015-02-12 2015-02 1 7 18 2015-02-25 2015-02 1 8 18 2015-03-04 2015-03 1 In second data frame there are some aggregated data by month from the first one: df2 = df1[df1['is_buy'] == 1].groupby(['id', 'month']).agg({'is_buy': np.sum}) print df2 id month buys 0

问题 i have a dataframe like this: df.head() Out[2]: price sale_date 0 477,000,000 1396/10/30 1 608,700,000 1396/10/30 2 580,000,000 1396/10/03 3 350,000,000 1396/10/03 4 328,000,000 1396/03/18 that it has out of bounds datetime so then i follow below to make them as period time df['sale_date']=df['sale_date'].str.replace('/','').astype(int) def conv(x): return pd.Period(year=x // 10000, month=x // 100 % 100, day=x % 100, freq='D') df['sale_date'] = df['sale_date'].str.replace('/','').astype(int)

问题 As I have searched in website to get the number of weekdays in python, but I need the date of the weekdays too. My input will be: start date = 01-03-2019 end_date = 15-03-2019 days = monday , tuesday Expected Output : which I need is to print the number of mondays and tuesdays along with the date. 回答1: Try this : start_date = '01-03-2019' # Considering 03 is the month, 01 is the day end_date = '15-03-2019' # Considering 03 is the month, 15 is the day start_date = [int(i) for i in start_date

问题 As I have searched in website to get the number of weekdays in python, but I need the date of the weekdays too. My input will be: start date = 01-03-2019 end_date = 15-03-2019 days = monday , tuesday Expected Output : which I need is to print the number of mondays and tuesdays along with the date. 回答1: Try this : start_date = '01-03-2019' # Considering 03 is the month, 01 is the day end_date = '15-03-2019' # Considering 03 is the month, 15 is the day start_date = [int(i) for i in start_date

问题 As I have searched in website to get the number of weekdays in python, but I need the date of the weekdays too. My input will be: start date = 01-03-2019 end_date = 15-03-2019 days = monday , tuesday Expected Output : which I need is to print the number of mondays and tuesdays along with the date. 回答1: Try this : start_date = '01-03-2019' # Considering 03 is the month, 01 is the day end_date = '15-03-2019' # Considering 03 is the month, 15 is the day start_date = [int(i) for i in start_date

问题 I have a data-frame and I want to send it in my Django template. dummy code in views.py : def graphs(request): df_new = pd.read_excel("/home/cms/cms/static/Sensorik.xlsx") times = df_new.loc[:, df_new.columns[0]].to_json(orient='records') # columns[0] contains datetime values data_color = df_georgian.loc[:, df_georgian.columns[2]] color = data_color.to_json(orient='records') context = { 'times': times, 'data_color': color, ... } return render(request, 'graphs/graphs.html', context) In my

问题 I have a data-frame and I want to send it in my Django template. dummy code in views.py : def graphs(request): df_new = pd.read_excel("/home/cms/cms/static/Sensorik.xlsx") times = df_new.loc[:, df_new.columns[0]].to_json(orient='records') # columns[0] contains datetime values data_color = df_georgian.loc[:, df_georgian.columns[2]] color = data_color.to_json(orient='records') context = { 'times': times, 'data_color': color, ... } return render(request, 'graphs/graphs.html', context) In my