csv

问题 I have large csv files with size more than 10 mb each and about 50+ such files. These inputs have more than 25 columns and more than 50K rows. All these have same headers and I am trying to merge them into one csv with headers to be mentioned only one time. Option: One Code: Working for small sized csv -- 25+ columns but size of the file in kbs. import pandas as pd import glob interesting_files = glob.glob("*.csv") df_list = [] for filename in sorted(interesting_files): df_list.append(pd.read

问题 I'm trying to figure out how to check an entire column to verify all values are integers, except one, using python pandas. One row name will always have a float num. CSV example: name, num random1,2 random2,3 random3,2.89 random4,1 random5,3.45 In this example, let's say 'random3's num will always be a float. So that fact that random5 is also a float, means the program should print an error to the terminal telling the user this. 回答1: Try this: if len(df.num.apply(type) == float) >= 2: print(f

问题 I have been given a PDF file with a form. The form is not formatted as a table. My requirement is to extract the form field values, and write them to a CSV file which can be imported into Excel. I have tried using the automated "Merge data files to Spreadsheet" menu item in Acrobat Pro, but the output includes both the labels and form field values. I am interested in mostly just the form field values. I would like to use JavaScript to extract the form data, and instruct JavaScript how to

问题 I have been given a PDF file with a form. The form is not formatted as a table. My requirement is to extract the form field values, and write them to a CSV file which can be imported into Excel. I have tried using the automated "Merge data files to Spreadsheet" menu item in Acrobat Pro, but the output includes both the labels and form field values. I am interested in mostly just the form field values. I would like to use JavaScript to extract the form data, and instruct JavaScript how to

问题 Seems a common issue to have a buggy CSV file when attempting to parse to an array, AR model import, etc. I haven't found a working solution other than open in MS Excel and save as every day (not good enough!). In a 60,000 row externally-provided, daily-updated csv file, there's an error: CSV::MalformedCSVError: Illegal quoting in line 95. (as an example). I'm happy to skip/forget the malformed row (i.e. it has only 1/60000th importance). First attempt is to use CSV.foreach or similar, and

问题 How can I write only first N rows or from P to Q rows to csv from pandas dataframe without subseting the df first? I cannot subset the data I want to export because of memory issues. I am thinking of a function which writes to csv row by row. Thank you 回答1: Use head- Return the first n rows. Ex. import pandas as pd import numpy as np date = pd.date_range('20190101',periods=6) df = pd.DataFrame(np.random.randn(6,4), index=date, columns=list('ABCD')) #wtire only top two rows into csv file print

问题 How can I write only first N rows or from P to Q rows to csv from pandas dataframe without subseting the df first? I cannot subset the data I want to export because of memory issues. I am thinking of a function which writes to csv row by row. Thank you 回答1: Use head- Return the first n rows. Ex. import pandas as pd import numpy as np date = pd.date_range('20190101',periods=6) df = pd.DataFrame(np.random.randn(6,4), index=date, columns=list('ABCD')) #wtire only top two rows into csv file print

问题 I have a webpage that accepts CSV files. These files may be created in a variety of places. (I think) there is no way to specify the encoding in a CSV file - so I can not reliably treat all of them as utf-8 or any other encoding. Is there a way to intelligently guess the encoding of the CSV I am getting? I am working with Python, but willing to work with language agnostic methods too. 回答1: There is no correct way to determine the encoding of a file by looking at only the file itself, but you

问题 I want to calculate the mean of column of all the csv in one directory, but when I run the function it give me the error of "Error in numeric(nc) : invalid 'length' argument". I believe that CSV files have n/a value but it shouldn't affect the calculate the number of column? pollutantmean <- function(directory, pollutant, id =1:332, removeNA = TRUE){ nc <- ncol(pollutant) means <- numeric(nc) for(i in 1:nc){ means[i] <- mean(pollutant[, i], na.rm = removeNA) } means } So here is my update

问题 I'm new to c++ after learning basic Object Oriented Programming in Java so I'm having a difficult time grasping memory deallocation. The assignment was to create a Weighted Directed Graph... I'm getting the error: "terminate called after throwing an instance of 'std::bad_alloc' what(): std::bad_alloc" when I run certain inputs through my code, and I'm having a difficult time figuring out what is causing it. I googled the error and found that it was a memory problem, so I attempted to go