I am currently writing a lager script to ease my life.
Right now I am reading raw values from cells from an excel.
So far so good.
These numbers need to be interpreted as seconds and then converted into minutes.
I tried my best with datetime but no luck.
Any suggestions?
elif auswahl == '2':
print("Some user friendly-text:")
excel_download = openpyxl.load_workbook(r'/Path/to/excel.xlsx')
sheet = excel_download.active
Grund_1 = sheet['B2'].value
Grund_2 = sheet['B3'].value
Grund_3 = sheet['B4'].value
Grund_4 = sheet['B5'].value
Grund_5 = sheet['B6'].value
Grund_6 = sheet['B7'].value
Zeit_in_Sekunden_1 = sheet['C2'].value
Zeit_in_Sekunden_2 = sheet['C3'].value
Zeit_in_Sekunden_3 = sheet['C4'].value
Zeit_in_Sekunden_4 = sheet['C5'].value
Zeit_in_Sekunden_5 = sheet['C6'].value
Zeit_in_Sekunden_6 = sheet['C7'].value
print("Du warst heute für", Zeit_in_Sekunden_1, Grund_1, "!")
break
My idea:
raw_seconds_from_C2 = sheet['C2'].value
Then somehow convert to minutes from raw_seconds_from_C2
I am really out of ideas as I then need to put the converted minutes into a print().
Divide the value by 60 to obtain minutes from seconds:
c2_minutes = sheet['C2'].value / 60
Thanks to #Alonso's comment on the question.
Related
I can try to set condition some data that is within the time picker in the datepicker. I got two problem
MY code was
def show_filter_date(start ,end):
print(start_dater.value)
print(end_dater.value)
time_df = (id_one[(id_one['_source.timestampstring']>pd.to_datetime(start))&(id_one['_source.timestampstring']<pd.to_datetime(end))])
#print(time_df.head(20))
# time_df = (id_one[(id_one['_source.timestampstring']>pd.to_datetime(start_dater.value))&(id_one['_source.timestampstring']<pd.to_datetime(end_dater.value))])
time_df.head(20)
layout = widgets.Layout(width='auto', height='40px')
start_dater = widgets.DatePicker(description='Pick a Start Date',disabled=False)
end_dater = widgets.DatePicker(description='Pick an End Date',disabled=False )
#display(widgets.HBox((start_dater, end_dater)))
#display(start_dater)
#display(end_dater)
#id_one.head()
#combine_date = widgets.HBox((start = start_dater, end = end_dater))
#country_selector = widgets.Dropdown(
interact(show_filter_date,start = start_dater , end = end_dater)
everytime i run the code it show Error
"Invalid comparison between dtype=datetime64[ns] and NoneType"
I have tried to assign default value like
start_dater = widgets.DatePicker(description='Pick a Start Date',disabled=False, year = 2020 ,month = 12, day = 1)
but it won't change to 2020/12/01
So, how can I get a value other than null?
I fail in interact for the datepicker in which
A) print(time_df.head(20))
B)
time_df = (id_one[(id_one['_source.timestampstring']>pd.to_datetime(start_dater.value))&(id_one['_source.timestampstring']<pd.to_datetime(end_dater.value))])
time_df.head(20)
Only (A) can be "interact" or "refresh" when I pick a day but not (B)
And for Question 2, when I put time_df.head(20) in the NEXT CELL it does work tho.......
But what i want is to show the result like in time_df
I would appreciate if any help
the id_one is something like
Index _source.hdrrId _source.hdrfId _source.hdrType \
199 1300 1234 1
_source.timestampstring
199 2020-11-06 09:36:04.800
Thanks!
Jeff
I replicated your first error with
id_one = pd.DataFrame(pd.date_range('20200101','20200202'), columns = ['_source.timestampstring'])
This is because you did not set a default value for the DatePicker. The value is None by default hence the error. Here is the fix (value argument is the default value):
start_dater = widgets.DatePicker(description='Pick a Start Date',disabled=False, value = datetime.date(2020,1,1))
end_dater = widgets.DatePicker(description='Pick an End Date',disabled=False, value = datetime.date(2020,2,1))
I cannot replicate your second error. My guess is you put print before the time_df = statement. You need to put the print after the line that calculates time_df
I have a csv file with date and time. I want to give specific timeinterval (60min) in between time range (start time and end time). I wrote a code with a date. But it gives me an error Number of samples, -5, must be non-negative. Then I checked with separate csv file with less data. Then I found that I have time like 9:53 , 10:20 ,11:42 .... Then when I'm dividing to find num_periods then its give me an error.
example
take date range like
2018 /8/6 start time is 6:00
2018/8/6 end time is 23:52
then it between I have time like 7:00, 8:52,10:42 so on.
after that in next day I have a time period like this.
So when I tried to find a num_periods then it give me this error.
I want to specify time in between this time_range
(start_time+time_interval(3600 in seconds (60min)) in between time_range)
Can anyone give me solution for this?
my code is,
time_interval = 3600
date_array = []
date_array.append(pd.to_datetime(data['date'][0]).date())
start_time = []
end_time = []
temp_date = pd.to_datetime(data['date'][0]).date()
start_time.append(pd.to_datetime(data['time'][0], format='%H:%M:%S').time())
for i in range(len(data['date'])):
cur_date = pd.to_datetime(data['date'][i]).date()
if( cur_date > temp_date):
end_time.append(pd.to_datetime(data['time'][i-1], format='%H:%M:%S').time())
start_time.append(pd.to_datetime(data['time'][i], format='%H:%M:%S').time())
date_array.append(cur_date)
temp_date = cur_date
end_time.append(pd.to_datetime(data['time'][len(data['date'])-1], format='%H:%M:%S').time())
datetime_array = []
for i in range(len(date_array)):
s_time = datetime.datetime.combine(date_array[i],start_time[i])
e_time = datetime.datetime.combine(date_array[i], end_time[i])
timediff = (e_time - s_time)
num_periods = int(timediff.total_seconds()/time_interval) +1
time_list = pd.date_range(start=s_time, end = e_time, periods=num_periods ).to_pydatetime()
datetime_array.extend(time_list)
error:
subset of my csv file
It looks like num_periods is negative:
num_periods = int(timediff.total_seconds()/time_interval) + 1
the easiest solution is to take the abs value instead:
num_periods = abs(int(timediff.total_seconds()/time_interval)) + 1
Note: that date_range supports ranges in reverse order (where start > end).
I'm in need of optimizing import of .xls files to matlab due to xlsread being very time consuming with large amount of files. Current xlsread script as follows:
scriptName = mfilename('fullpath');
[currentpath, filename, fileextension]= fileparts(scriptName);
xlsnames = dir(fullfile(currentpath,'*.xls'));
xlscount = length(xlsnames);
xlsimportdata = zeros(7,6,xlscount);
for k = 1:xlscount
xlsimport = xlsread(xlsnames(k).name,'D31:I37');
xlsimportdata(:,1:size(xlsimport,2),k) = xlsimport;
end
I have close to 10k files per week that needs processing and with approx. 2sec per file processed on my current workstation, it comes in at about 5½ hours.
I have read that ActiveX can be used for this purpose however that is far beyond my current programming skills and have not been able to find a solution elsewhere. Any help on how to make this would be appreciated.
If it is simple to perform with ActiveX (or other proposed method), I would also be interested in data on cells D5 and G3, which I am currently grabbing from 'xlsnames(k,1).name' and 'xlsnames(k,1).date'
EDIT: updated to reflect the solution
% Get path to .m script
scriptName = mfilename('fullpath');
[currentpath, filename, fileextension]= fileparts(scriptName);
% Generate list of .xls file data
xlsnames = dir(fullfile(currentpath,'*.xls'));
xlscount = length(xlsnames);
SampleInfo = cell(xlscount,2);
xlsimportdata = cell(7,6,xlscount);
% Define xls data ranges to import
SampleID = 'G3';
SampleRuntime = 'D5';
data_range = 'D31:I37';
% Initiate progression bar
h = waitbar(0,'Initiating import...');
% Start actxserver
exl = actxserver('excel.application');
exlWkbk = exl.Workbooks;
for k = 1:xlscount
% Restart actxserver every 100 loops due limited system memory
if mod (k,100) == 0
exl.Quit
exl = actxserver('excel.application');
exlWkbk = exl.Workbooks;
end
exlFile = exlWkbk.Open([dname filesep xlsnames(k).name]);
exlSheet1 = exlFile.Sheets.Item('Page 0');
rngObj1 = exlSheet1.Range(SampleID);
xlsimport_ID = rngObj1.Value;
rngObj2 = exlSheet1.Range(SampleRuntime);
xlsimport_Runtime = rngObj2.Value;
rngObj3 = exlSheet1.Range(data_range);
xlsimport_data = rngObj3.Value;
SampleInfo(k,1) = {xlsimport_ID};
SampleInfo(k,2) = {xlsimport_Runtime};
xlsimportdata(:,:,k) = xlsimport_data;
% Progression bar updater
progress = round((k / xlscount) * 100);
importtext = sprintf('Importing %d of %d', k, xlscount);
waitbar(progress/100,h,sprintf(importtext));
disp(['Import progress: ' num2str(k) '/' num2str(xlscount)]);
end
%close actxserver
exl.Quit
% Close progression bar
close(h)
Give this a try. I am not an ActiveX Excel guru by any means. However, this works for me for my small amount of test XLS files (3). I never close the exlWkbk so I don't know if memory usage is building or if it automatically cleaned up when descoped after the next is opened in its place ... so use at your own risk. I am seeing an almost 2.5x speed increase which seems promising.
>> timeit(#getSomeXLS)
ans =
1.8641
>> timeit(#getSomeXLS_old)
ans =
4.6192
Please leave some feedback if this work on large number of Excel sheets because I am curious how it goes.
function xlsimportdata = getSomeXLS()
scriptName = mfilename('fullpath');
[currentpath, filename, fileextension]= fileparts(scriptName);
xlsnames = dir(fullfile(currentpath,'*.xls'));
xlscount = length(xlsnames);
xlsimportdata = zeros(7,6,xlscount);
exl = actxserver('excel.application');
exlWkbk = exl.Workbooks;
dat_range = 'D31:I37';
for k = 1:xlscount
exlFile = exlWkbk.Open([currentpath filesep xlsnames(k).name]);
exlSheet1 = exlFile.Sheets.Item('Sheet1'); %Whatever your sheet is called.
rngObj = exlSheet1.Range(dat_range);
xlsimport = cell2mat(rngObj.Value);
xlsimportdata(:,:,k) = xlsimport;
end
exl.Quit
Say that I have a time value given, for example: 2012-03-28_15:10:00
and then I have a sting that stores multiple time values:
2012-03-28_14:00:00
2012-03-28_14:10:00
2012-03-28_14:20:00
2012-03-28_14:30:00
2012-03-28_14:40:00
2012-03-28_14:50:00
2012-03-28_15:00:00
2012-03-28_15:05:00
2012-03-28_15:20:00
2012-03-28_15:30:00
I want to find the time value in the string that is the closest to the original time value.
Does anyone know how this can be done in matlab?
Code
data1 = '2012-03-28_15:10:00'
data2 = [
'2012-03-28_14:00:00'
'2012-03-28_14:10:00'
'2012-03-28_14:20:00'
'2012-03-28_14:30:00'
'2012-03-28_14:40:00'
'2012-03-28_14:50:00'
'2012-03-28_15:00:00'
'2012-03-28_15:05:00'
'2012-03-28_15:20:00']
[~,ind1] = min(abs(datenum(data2)-datenum(data1)));
closest_time = data2(ind1,:)
Output
closest_time =
2012-03-28_15:05:00
Extended Part: If you have many dates, as a char matrix too and to be compared to the list, then using a bsxfun approach might be a better solution, as it avoids loops. This is shown below -
Code
data1 = [
'2012-03-28_14:02:00'
'2012-03-28_14:11:00'
'2012-03-28_14:23:00'
'2012-03-28_14:32:00']
data2 = [
'2012-03-28_14:00:00'
'2012-03-28_14:10:00'
'2012-03-28_14:20:00'
'2012-03-28_14:30:00'
'2012-03-28_14:40:00'
'2012-03-28_14:50:00'
'2012-03-28_15:00:00'
'2012-03-28_15:05:00'
'2012-03-28_15:08:00']
[~,ind1] = min(abs(bsxfun(#minus,datenum(data2),datenum(data1)')));
closest_time = data2(ind1,:)
Output
closest_time =
2012-03-28_14:00:00
2012-03-28_14:10:00
2012-03-28_14:20:00
2012-03-28_14:30:00
The data in my Excel files is supposed to be contentious (index in the first column). But some data is missing in the file. For example, # 5, and 6 are missing between $ 4 and 7. My purpose are (1) identify the file with missing data and (2) if data is missing insert rows to make it continuous. Can anyone tell me how to add in rows in the existing data? Using xlswrite I can only add in rows at the end of the file or replace some rows.
EDIT 1:
I have another set of file in which the index is not so direct. The first 3 columns are described below (as shown in the Excel file):
Column 1：Year: 2003 (read as number in matlab)
Column 2：Date: 1-Sep (read as text in matlab)
Column 3：Time: 1:00 (1:00 read as number 0.04167 and 2:00 read as 0.0833, not sure how it works)
Then the way to tell if it is continuous will be quite complicate since there will be different years, months, and days. Could you give some hint on this?
Basically you need to read the entire data, preferably in raw(cell) format, add the missing rows(with respect to the indices) and write back.
Based on your question, this code might work -
% NOTE: We are assuming that the indexing starts with 1
% Read data from input excel file with missing indices
[num,txt,raw] = xlsread('input.xls');
% Error-checking
if (size(num,1)-num(end,1)~=0)
disp('At least one index is missing!');
end
% Expand data such that all indices are covered.
data1=NaN(num(end,1),size(raw,2));
data1(:,1) = 1:num(end,1);
data1=num2cell(data1);
k1=1;
for k = 1:num(end,1)
if(num(k1,1)==k)
data1(k,:)= raw(k1,:);
k1 = k1+1;
end
end
% Write data
xlswrite('output.xls',data1);
EDIT 1:
In view of your new requirements, additional code is added next.
Please note few things about this code -
The code adds data for every year and not from a specific month, date and time to another specific month, date and time. If you wish to achieve that, please edit the associated
function - 'create_comp_sheet'.
It saves an intermediate file named - 'proper_base_data.xls', which maybe deleted at the end of the code.
%% MAIN CODE - CODE1.M
INPUT_FILENAME = 'input.xls'; % Excel file that has some missing year,date and time info
OUTPUT_FILENAME = 'output.xls'; % Excel file that has data from the input file along with all the missing year,date and time info
%% Base data
start_year=2003;
end_year=2005;
proper_base_data = create_comp_sheet(start_year,end_year);
xlswrite('proper_base_data.xls',proper_base_data);
[num,txt,raw] = xlsread('proper_base_data.xls');
base_data=cell(size(num,1),1);
for row_ID = 1:size(num,1)
base_data(row_ID) = {strcat(num2str(cell2mat(raw(row_ID,1))),'-', cell2mat(raw(row_ID,2)),'-',num2str(round(24*cell2mat(raw(row_ID,3)))))};
end
%% Input data
[num,txt,raw] = xlsread(INPUT_FILENAME);
input_data=cell(size(num,1),1);
for row_ID = 1:size(num,1)
input_data(row_ID) = {strcat(num2str(cell2mat(raw(row_ID,1))),'-', cell2mat(raw(row_ID,2)),'-',num2str(round(24*cell2mat(raw(row_ID,3)))))};
end
%% Setup final data
final_data = num2cell(NaN(size(proper_base_data,1),size(raw,2)));
final_data(:,1:3) = proper_base_data;
for k1=1:size(input_data,1)
for k2=1:size(base_data,1)
if strcmp(cell2mat(base_data(k2)),cell2mat(input_data(k1)))
final_data(k2,4:end) = raw(k1,4:end);
end
end
end
%% Write final data to excel
xlswrite(OUTPUT_FILENAME,final_data);
Associated function -
function data1 = create_comp_sheet(start_year,end_year)
months_string = {'Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'};
date_count = [31 28 31 30 31 30 31 31 30 31 30 31];
num_hours = 24;
data1=[];
for year_ID = start_year:end_year
for month_ID = 1:numel(months_string)
days_per_month = date_count(month_ID);
if rem(year_ID,4)==0 && month_ID ==2
days_per_month = days_per_month+1;
end
for date_ID = 1:days_per_month
year = repmat({num2str(year_ID)},[num_hours 1]);
date = repmat({strcat(num2str(date_ID),'-',char(months_string(month_ID)))},[num_hours 1]);
time=cell(num_hours,1);
for k = 1:num_hours
time(k) = {strcat(num2str(k),':00')};
end
data1 = [data1 ; [year date time]];
end
end
end
return;
Hope this saves all your troubles!