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[英]How to create separate Pandas DataFrames for each CSV file and give them meaningful names?
[英]How to create separate csv file for each sql query in python?
我在不同文件中有3个sql查询。 我试图一一运行所有sql查询。 但每个SQL查询的输出都保存在单个csv文件中。 所以我想将每个查询结果保存在单独的csv文件中。
path1 = "D:/Users/SPate233/Downloads/NS dashboard/sql_query/*.txt"
files = glob.glob(path1)
for name in files:
try:
with open(name) as f:
sql_query = f.read()
cur.execute(sql_query)
result = cur.fetchall()
with open("output.csv", 'w') as fp:
a = csv.writer(fp, delimiter=',')
a.writerow([i[0] for i in cur.description])
a.writerows(result)
except:
print("error")
发生这种情况是因为您每次都覆盖相同的csv。
path1 = "D:/Users/SPate233/Downloads/NS dashboard/sql_query/*.txt"
files = glob.glob(path1)
i = 1
for name in files:
try:
with open(name) as f:
sql_query = f.read()
cur.execute(sql_query)
result = cur.fetchall()
with open("output_%s.csv" % i, 'w') as fp:
a = csv.writer(fp, delimiter=',')
a.writerow([i[0] for i in cur.description])
a.writerows(result)
i+=1
except:
print("error")
您继续写入相同的CSV文件。 你为什么不尝试这样的事情:
path1 = "D:/Users/SPate233/Downloads/NS dashboard/sql_query/*.txt"
files = glob.glob(path1)
file_list = ["file1.csv", "file2.csv"]
for iterator, name in enumerate(files):
try:
with open(name) as f:
sql_query = f.read()
cur.execute(sql_query)
result = cur.fetchall()
with open(file_list[iterator], 'w') as fp:
a = csv.writer(fp, delimiter=',')
a.writerow([i[0] for i in cur.description])
a.writerows(result)
except:
print("error")
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