Question

我有CSV文件Sales_In.csv，DataFrame是：

Sales_Region     Dollar_value
East             500
west             500
south            500
North            2000

我正在使用熊猫

import pandas as pd
import UUID

df= pd.read_csv('Sales_In.csv')
low_sales =df[(df['Dollar_value'] >=500) & (df['Dollar_value']<=1000)]

for index,row in low_sales.iterrows():
    for loop in range(10):
        print(uuid.uuid1().hex[:8],"REP"+str(uuid.uuid4().hex[:9]),row['Sales_Region'])

以上代码为我提供了如下输出

279418fe HCP6eacac48a East
279418ff HCP6fb7d0ec2 East
27941900 HCP21cb84de3 East
27941901 HCP9b6a34bf0 East
27941902 HCP6aa9f0e20 East
27941903 HCP6fa5e3201 East
27941904 HCPabecf8c42 East
27941905 HCP0922c8acc East
27941906 HCPea9e91d7c East
27941907 HCP95f8dbfb9 East

我想用以下标题将其写到csv文件中

CUS_KEY   Unique Key    Sales_Region
279418fe   HCP6eacac48a  East
279418ff   HCP6fb7d0ec2  East
27941900   HCP21cb84de3  East
...................

我是python的新手，有点被困在这帮助我了！

Answer 1

使用列表推导创建值的元组，由构造器创建DataFrame，最后由to_csv创建文件：

low_sales =df[(df['Dollar_value'] >=500) & (df['Dollar_value']<=1000)]

L = [(uuid.uuid1().hex[:8],"REP"+str(uuid.uuid4().hex[:9]),x)
      for x in low_sales['Sales_Region'] for i in range(10)]

df = pd.DataFrame(L, columns=['CUS_KEY','Unique Key','Sales_Region'])
print (df.head(10))
    CUS_KEY    Unique Key Sales_Region
0  96cdb1f8  REPf2fedbce5         East
1  96cdb1f9  REPfc6d311f4         East
2  96cdb1fa  REPa31a28651         East
3  96cdb1fb  REP4f4689565         East
4  96cdb1fc  REP9e0a484a7         East
5  96cdb1fd  REPa8f763796         East
6  96cdb1fe  REP442ad19dd         East
7  96cdb1ff  REPa317fa7b0         East
8  96cdb200  REPb14ca95b9         East
9  96cdb201  REP60c31eb67         East

df.to_csv(file, index=False)

如果要使用您的代码：

L = []
for index,row in low_sales.iterrows():
    for loop in range(10):
        L.append((uuid.uuid1().hex[:8],"REP"+str(uuid.uuid4().hex[:9]),row['Sales_Region']))

df = pd.DataFrame(L, columns=['CUS_KEY','Unique Key','Sales_Region'])

Answer 2

尝试一下：

将列分配给df。

df.columns = ['CUS_KEY','Unique Key','Sales_Region']

然后写入csv。

df.to_csv('abc.csv', index=False, header=True)

Answer 3

================================================ =================

对于核心python，您可以使用csv追加新行。确保file.csv将位于正确的文件夹中

import csv
row = ['4', 'Anoop', 'Chamba']

with open('file.csv', 'a') as csvFile:
    writer = csv.writer(csvFile)
    writer.writerow(row)

csvFile.close()

================================================ ======================

在熊猫中，以下代码可以解决您的问题：-

df = pd.read_csv("myfile.csv")
df['new_column'] = 'some_value'
df.to_csv('myfile.csv')

Answer 4

我认为，您需要这样做：

df_2 = pd.DataFrame()
for loop in low_sales.Sales_Region:
    df_2 = df_2.append({'CUS_KEY':uuid.uuid1().hex[:8],
                        'Unique Key':"REP"+str(uuid.uuid4().hex[:9]),
                        'Sales_Region':loop},ignore_index=True)

然后：

df_2.to_csv('New_df.csv', index=False, header=True)

在CSV文件python中用现有的迭代行追加新行

4 个答案: