involves the calculation of a large amount of data there are multiple loops nested within the use of pandas for calculation extremely slow is there any effective way to speed up? ...
I want to add several pieces of data to an excel through Pandas. Check the document and find Pandas.ExcelWriter ( http: pandas.pydata.org pand...) has this function, but if you need to append data to excel When using, set the parameter mode to ...
use Pandas to analyze an excel data, which contains the excel date field date , stored values such as 2018-12-31 , and use pd.read_excel to read all excel data. Since the values in the table are entered artificially, in order to avoid potential readi...
the reason has been found. The order of variables from append to the data box will be adjusted automatically when the column tag of DataFrame is not set beforehand. df = pd.DataFrame() series=pd.Series([3,4,1,6],index=[ b , a , d , c ]) df=df.a...
pandas6Excel ...
two columns of existing data, as shown in the following figure: then I want to delete the data in column a that matches a regular expression (such as the beginning of 0002). How should I write it? add: the above is just an example, because it doe...
encountered a problem and simplified it. has a dataframe df = pd.DataFrame([[ a , 1, c ], [ a , 3, a ], [ a , 2, b ], [ c , 3, a ], [ c , 2, b ], [ c , 1, c ], [ b , 2, b ], [ ...
df = pd.DataFrame({ key1 : [ a , a , a , b , b ], key2 : [ c , d , c , c , d ], data : [1,10,2,3,30]}) >>> df key1 key2 data 0 a c 1 1 a d 10 2 a c 2 3 b c 3 4 ...
know the start time and end time of each sample, as shown in the following figure: hu is the unique value of the sample. It is known that time1 and time2 are the start time and end time of the behavior, respectively. Now, we want to count the number...
use pandas s read_csv to read a dataset import pandas as pd dfoff = pd.read_csv (xxx.csv , keep_default_na=False) pd.set_option ( display.max_columns , None) print (dfoff.head (3)) found that he has 6 columns of data User_id print(dfof...
recently, I want to process the form for analysis. Due to the lack of experience in dealing with sql or csv, I have encountered the following problems and asked to solve them: question 1: companyID fresh 23865 13-2 23866 10-3 23867 8-...
pandas read_sql is too slow 10W rows of data take about 10 seconds. Is there an optimization plan ? ...
I wrote a part here, that is to say, first convert the original df into a dictionary, and then create a new dictionary and then operate on these two dictionaries, but there seems to be a problem with the result of a large amount of data . ...
how to query data in B dataframe according to the ID, of A dataframe in pandas, An and B tables have the same ID column. Similar to SQL s column-level subquery: select * from t_class where c_id in (select c_class_id from t_student) , An and B have an o...
problem description A pit when performing operations in the actual development of pandas! -------------------------------------------------------------------------------- age name 0 10 abc 1 11 None 2 9 def ---------------------------...
< H2 > Development environment < H2 > python 3.6 pandas 0.23.3 has a DataFrame, as follows: import pandas as pd arr = [[10,10,1],[22,24.2,1.1],[15,15,1],[9,8.1,0.9],[50,55,1.1]] df = pd.DataFrame(arr,columns=[ volume , amount , price ]) ...
A function that follows lines in conditional Filter pandas. works fine for non-empty dataframe, but for empty dataframe, Filter with column name , empty datafram missing column name the problem is repeated as follows: In [5]: t1 = pd.DataFrame(co...
1. When I am converting the real data of two dataframe tables into numpy data for column content comparison, I encounter the following situations: input: individual elements of different arrays d12.values [0] [0], d12.values [1] [0], d11.values [...
Ladies and Gentlemen, I would like to ask you a Pandas grouping question, which I feel is more complicated. df = pd.DataFrame({"Date":pd.date_range(start= 2018-08-17 08:10:30 ,periods=15,freq= s ,normalize=True),"Category":list(...
at present, I am building a consolidated financial statement system, which grabs numbers from the financial system and then does data cleaning and calculation, in which the cleaning phase is mainly completed by pandas. In the captured data, the numbers ...