csv

问题 I am trying to learn about Dataframes but I'm still a beginner. Let's say I have a DataFrame that contains two columns: Name Description Am Owner of Am BQ Employee at BQ JW Employee somewhere I want to check if the name is also a part of the description, and if so keep the row. If it's not, delete the row. In this case, it will delete the 3rd row (JW Employee somewhere) 回答1: Try this: df[df.apply(lambda x: x['Name'] in x['Description'], axis = 1)] 回答2: s='|'.join(df.Name)#Join the search

问题 I am using Python 3.5. I have several csv files: The csv files are named according to a fixed structure. They have a fixed prefix (always the same) plus a varying filename part: 099_2019_01_01_filename1.csv 099_2019_01_01_filename2.csv My original csv files look like this: filename1-Streetname filename1-ZIPCODE TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT Street1 2012932 Street2 3023923 filename2-Name filename2-Phone TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT TEXT

问题 I am trying to fetch the execution details of one user, and all those data i am capturing in a JSON and saving it , i want to convert this from JSON and write all the data from JSON to a csv file, Delimiter = ' , ' import os import re import json import warnings import urllib.request import csv warnings.filterwarnings('ignore', message='Unverified HTTPS request') url = "http://machine245.local:4450/api/35/project/ProjectName01/executions" headers = { 'Accept': 'application/json', 'X-Rundeck

问题 I am trying to fetch the execution details of one user, and all those data i am capturing in a JSON and saving it , i want to convert this from JSON and write all the data from JSON to a csv file, Delimiter = ' , ' import os import re import json import warnings import urllib.request import csv warnings.filterwarnings('ignore', message='Unverified HTTPS request') url = "http://machine245.local:4450/api/35/project/ProjectName01/executions" headers = { 'Accept': 'application/json', 'X-Rundeck

问题 I am trying to import a list of chemicals from a txt file which is spaced (not tabbed). NO FORMULA NAME CAS No A B C D TMIN TMAX code ngas@TMIN ngas@25 C ngas@TMAX 1 CBrClF2 bromochlorodifluoromethane 353-59-3 -0.0799 4.9660E-01 -6.3021E-05 -9.0961E-09 200 1500 2 96.65 142.14 572.33 2 CBrCl2F bromodichlorofluoromethane 353-58-2 4.0684 4.1343E-01 1.6576E-05 -3.4388E-08 200 1500 2 87.14 127.90 545.46 3 CBrCl3 bromotrichloromethane 75-62-7 7.3767 3.5056E-01 6.9163E-05 -4.9571E-08 200 1500 2 79

问题 I am trying to import a list of chemicals from a txt file which is spaced (not tabbed). NO FORMULA NAME CAS No A B C D TMIN TMAX code ngas@TMIN ngas@25 C ngas@TMAX 1 CBrClF2 bromochlorodifluoromethane 353-59-3 -0.0799 4.9660E-01 -6.3021E-05 -9.0961E-09 200 1500 2 96.65 142.14 572.33 2 CBrCl2F bromodichlorofluoromethane 353-58-2 4.0684 4.1343E-01 1.6576E-05 -3.4388E-08 200 1500 2 87.14 127.90 545.46 3 CBrCl3 bromotrichloromethane 75-62-7 7.3767 3.5056E-01 6.9163E-05 -4.9571E-08 200 1500 2 79

问题 I am really new to php and everything I have learned is from my school textbook and online research. With that said I am trying to complete an assignment and I am stuck on the last part. for the final part the assignment says to "Create a PHP script that will dump the contents of the employee table into CSV text file that has comma separated values for each record. Each new record should begin on a new line" . I have tried many online tutorials but none of them teach how to put this event in

问题 I have a really large csv file about 10GB. When ever I try to read in into iPython notebook using data = pd.read_csv("data.csv") my laptop gets stuck. Is it possible to just read like 10,000 rows or 500 MB of a csv file. 回答1: It is possible. You can create an iterator yielding chunks of your csv of a certain size at a time as a DataFrame by passing iterator=True with your desired chunksize to read_csv. df_iter = pd.read_csv('data.csv', chunksize=10000, iterator=True) for iter_num, chunk in

问题 I have a really large csv file about 10GB. When ever I try to read in into iPython notebook using data = pd.read_csv("data.csv") my laptop gets stuck. Is it possible to just read like 10,000 rows or 500 MB of a csv file. 回答1: It is possible. You can create an iterator yielding chunks of your csv of a certain size at a time as a DataFrame by passing iterator=True with your desired chunksize to read_csv. df_iter = pd.read_csv('data.csv', chunksize=10000, iterator=True) for iter_num, chunk in

问题 Actually started using django-import-export latest version. Wanted to know where exactly we can override to skip certain rows of the csv from being imported based on current user or the domains from a list of domains he can import data from the csv. How exactly to customize which of the methods to override and how? In my ModelResource, I have created the list of domains for the current user, and which method of the import-export do I check this and skip the rows from being imported? class