重新排列 CSV 列

Question

当创建 CSV 文件时，列并没有像我希望的那样位于正确的位置。例如，列“Period”（变量为“RD”）是文件中的第二列等。

有没有办法将每列的位置设置为我想要的位置？

我的代码：

from datetime import datetime
from elasticsearch import Elasticsearch
import csv

es = Elasticsearch(["9200"])


res = es.search(index="search", body=
                {
                    "_source": ["VT","NCR","N","DT","RD"],
                    "query": {

                        "bool": {
                            "must": [{"range": {"VT": {
                                            "gte": "now/d",
                                            "lte": "now+1d/d"}}},

                                {"wildcard": {"user": "mike*"}}]}}},size=10)


csv_file = 'File_' + str(datetime.now().strftime('%Y_%m_%d - %H.%M.%S')) + '.csv'


header_names = { 'VT': 'Date', 'NCR': 'ExTime', 'N': 'Name', 'DT': 'Party', ' RD ': 'Period'}



with open(csv_file, 'w', newline='') as f:
    header_present  = False
    for doc in res['hits']['hits']:
        my_dict = doc['_source']
        if not header_present:
            w = csv.DictWriter(f, my_dict.keys())
            w.writerow(header_names,) 
            header_present = True
             w.writerow(my_dict)

Answer 1

使用 pandas 非常简单：

import pandas as pd


# Read csv / tab-delimited in this example
df = pd.read_csv('example.csv', sep='\t')

print df

   A  B  C
0  4  5  9
1  4  5  9
2  4  5  9
3  4  5  9

# Reorder columns
df = df[['C', 'A', 'B']]

print df

   C  A  B
0  9  4  5
1  9  4  5
2  9  4  5
3  9  4  5

# Write csv / tab-delimited
df.to_csv('example.csv', sep='\t')

Answer 2

字典没有排序，如果你想强制列排序，你需要明确指定

import csv
headers = ['Party', 'Period', 'Date', 'ExTime', 'Name'] # Don't use my_dict.keys()
with open('header.csv', 'w') as f:
    w = csv.DictWriter(f, fieldnames=headers)
    w.writeheader()

见

$ python sample.py && cat header.csv
Party,Period,Date,ExTime,Name

并且当你调用w.writerow(my_dict) 时，字典会根据标题进行排序。

row = {'Period':2, 'Date':3, 'Name':5, 'Party': 1, 'ExTime':4}
w.writerow(row)

输出

Party,Period,Date,ExTime,Name
1,2,3,4,5

Answer 3

当您处理 csv 文件时，最好将 pandas 用于您的应用程序。

import pandas as pd

# Let your file have 4 columns named c1, c2, c3 and c4
# And assume you want to reorder it to c2, c3, c1, c4

data_frame = pd.read_csv('filename.csv', delimiter=',') # reading csv file as data frame with pandas

new_data_frame = data_frame[['c2', 'c3', 'c1', 'c4']] # reordered the dataframe and stored in new_data_frame

# If you want to save the result to new csv file

new_data_frame.to_csv('altered.csv', index=None)

在您的情况下，假设列和分隔符的顺序是“，”

import pandas as pd

csv_file_name = 'File_' + str(datetime.now().strftime('%Y_%m_%d - %H.%M.%S')) + '.csv'

data_frame = pd.read_csv(csv_file_name, delimiter=',') # change delimiter to '\t' if needed

new_data_frame = data_frame[['Party', 'Period', 'Date', 'ExTime', 'Name']]

new_data_frame.to_csv('filename.csv', index=None)

Answer 4

import pandas as pd

df  = pd.read_csv('pokemon_data.csv')`enter code here`

'Name', 'Type 1', 'Type 2', 'HP', 'Attack', 'Defense', 'Sp. Atk','Sp. Def', 'Speed', 'Generation', 'Legendary'

（我的数据框由相同顺序的相同列名组成）

df['Total']=df.iloc[:,4:10].sum(axis=1)

`'Name', 'Type 1', 'Type 2', 'HP', 'Attack', 'Defense', 'Sp. Atk','Sp. Def', 'Speed', 'Generation', 'Legendary', 'Total'`

（添加一个新列 Total 是 hp、attack、defence、sp.atk、sp.def、speed 的总和）

cols = list(df.columns.values)
df = df[cols[0:4]+[cols[-1]]+cols[4:12]]

'Name', 'Type 1', 'Type 2','Total', 'HP', 'Attack', 'Defense', 'Sp. Atk','Sp. Def', 'Speed', 'Generation', 'Legendary'

（移动“总计”列）