I'm new to python and working on analyzing large data sets which involved merging csv files, they all contain the same labeled rows but with different amounts of columns. I don't have much but this is my current code, any help is greatly appreciated.
import csv
import pandas as pd
file1 = 'C:\\Users\\User\\Documents\\Ubiome csv Kit #\\107-078-414.csv'
file2 = 'C:\\Users\\User\\Documents\\Ubiome csv Kit #\\109-080-426.csv'
reader1 = csv.reader(open(file1))
reader2 = csv.reader(open(file2))
reader1 = csv.reader(open(file1))
reader2 = csv.reader(open(file2))
From the pandas docs: https://pandas.pydata.org/pandas-docs/stable/merging.html
import pandas as pd
df1 = pd.read_csv(file1)
df2 = pd.read_csv(file2)
merged_df = pd.concat([df1, df2], axis = 1, join = 'outer')
import pymysql.cursors
import re
import csv
import collections
import glob
# Variables
total_record = []
headerCount = 0
for file in glob.glob("*.csv"):
print(file)
with open(file, 'r') as f:
reader = csv.reader(f)
list_record = list(reader)
if headerCount == 0:
headerCount = 1
total_record.extend(list_record)
else:
list_record.pop(0)
total_record.extend(list_record)
with open('combine.csv', 'w') as csvFile:
writer = csv.writer(csvFile)
writer.writerows(total_record)
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