csv

问题 I would like to convert a csv file into json with nested objects and nested array. The sample csv looks like below. My csv structure can be dynamic, but I am ok to keep it static to get the required format below. I know there are so many answers to similar questions, but none addressing my specific issue of nested objects. Id,name,nestedobject/id,nestedarray/0/name 1,name,2,namelist 2,name1,3,namelist1 I want the json like below, specifically having trouble with column 3 & 4 (nested objects)

问题 Here is a template of my JSON: { "field 1": [ { "id": "123456" }, { "about": "YESH" }, { "can_post": true }, { "category": "Community" } ], "field 2": [ { "id": "123456" }, { "about": "YESH" }, { "can_post": true }, { "category": "Community" } ] } I would like to convert this JSON into a csv in the following format using Python: 0 field 1, id, about, can_post, category 1 field 2, id, about, can_post, category I tried using pandas to read_json and then to_csv but it didn't work. Thanks 回答1:

问题 I like to read two csv files from a particular folder into two separate dataframes. The two file names are: 23314621_MACI_NAV.CSV and 23314623_MACI_Holding.CSV The file second part of the file names are fixed MACI_NAV.CSV and MACI_Holding.CSV, however the first part of the file name which are numbers change everyday. I like to read them into two different dataframe by trying this: import pandas as pd import glob msci_folder = 'N:/Operation/Daily CDS E_Report/CDS/MACI/' mscifile = glob.glob

问题 I like to read two csv files from a particular folder into two separate dataframes. The two file names are: 23314621_MACI_NAV.CSV and 23314623_MACI_Holding.CSV The file second part of the file names are fixed MACI_NAV.CSV and MACI_Holding.CSV, however the first part of the file name which are numbers change everyday. I like to read them into two different dataframe by trying this: import pandas as pd import glob msci_folder = 'N:/Operation/Daily CDS E_Report/CDS/MACI/' mscifile = glob.glob

问题 I'm currently trying to open a 48GB csv on my computer. Needless to say that my RAM does no support such a huge file, so I'm trying to filter it before opening. From what I've researched, the most appropriate way to do so in R is using the sqldf lib, more specifically the read.csv.sql function: df <- read.csv.sql('CIF_FOB_ITIC-en.csv', sql = "SELECT * FROM file WHERE 'Year' IN (2014, 2015, 2016, 2017, 2018)") However, I got the following message: Erro: duplicate column name: Measure As SQL is

问题 When trying to use the IMPORTDATA function for this file: https://www.kaggle.com/stefanoleone992/fifa-20-complete-player-dataset#players_20.csv An unexpected error occurs that says it is impossible to import data into the spreadsheet. Is there any other way that I can bring this data to my spreadsheet? This data would be very important to the work I'm doing. It would save me from almost 3 months of work to be able to type and copy everything and then filtering according to my need. It would

问题 If we have a CSV file like this: `firstName, lastName Jim, Carrey Stephen, Colbert` Papaparse will output the dynamically typed result like this: {firstName: 'Jim', ' lastName': '30000'} In order to just get {firstName: 'Jim', lastName...} PapaParse 5.0.0 has a transformHeaders option, but there's no documentation on how to achieve this result yet. Anyone have a transformHeader snippet that does this? 回答1: This ended up doing the trick: const config = { delimiter: ",", header: true,

问题 If we have a CSV file like this: `firstName, lastName Jim, Carrey Stephen, Colbert` Papaparse will output the dynamically typed result like this: {firstName: 'Jim', ' lastName': '30000'} In order to just get {firstName: 'Jim', lastName...} PapaParse 5.0.0 has a transformHeaders option, but there's no documentation on how to achieve this result yet. Anyone have a transformHeader snippet that does this? 回答1: This ended up doing the trick: const config = { delimiter: ",", header: true,

问题 I'm using some awk inside a bash script that's handling CSVs. The awk does this: ORIG_FILE="score_model.csv" NEW_FILE="updates/score_model.csv" awk -v d="2017_01" -F"," 'BEGIN {OFS = ","} {$(NF+1)=d; print}' $ORIG_FILE > $NEW_FILE Which does this transformation: # before model_description, type, effective_date, end_date Inc <= 40K, Retired, 08/05/2016, 07/31/2017 Inc > 40K Age <= 55 V5, Retired, 04/30/2016, 07/31/2017 Inc > 40K Age > 55 V5 , Retired, 04/30/2016, 07/31/2017 # after, bad model

问题 I'm using some awk inside a bash script that's handling CSVs. The awk does this: ORIG_FILE="score_model.csv" NEW_FILE="updates/score_model.csv" awk -v d="2017_01" -F"," 'BEGIN {OFS = ","} {$(NF+1)=d; print}' $ORIG_FILE > $NEW_FILE Which does this transformation: # before model_description, type, effective_date, end_date Inc <= 40K, Retired, 08/05/2016, 07/31/2017 Inc > 40K Age <= 55 V5, Retired, 04/30/2016, 07/31/2017 Inc > 40K Age > 55 V5 , Retired, 04/30/2016, 07/31/2017 # after, bad model