我的代碼合并 csv 文件并使用 pandas 刪除重復(fù)項。是否可以向單個合并文件添加帶有值的附加標(biāo)頭？應(yīng)調(diào)用附加標(biāo)頭Host Alias并應(yīng)對應(yīng)于Host Name例如Host Name是dpc01n1和對應(yīng)的Host Alias應(yīng)該dev_dom1 Host Name是dpc02n1和對應(yīng)的Host Alias應(yīng)該是dev_dom2 等。這是我的代碼from glob import globimport pandas as pdclass bcolors: HEADER = '\033[95m' OKBLUE = '\033[94m' OKGREEN = '\033[92m' WARNING = '\033[93m' FAIL = '\033[91m' ENDC = '\033[0m' BOLD = '\033[1m' UNDERLINE = '\033[4m'input_path = r'C:\Users\urale\Desktop\logs'output_path = r'C:\Users\urale\Desktop\logs' + '\\'output_name = 'output.csv'stock_files = sorted(glob(input_path + '\pc_dblatmonstat_*_*.log'))print(bcolors.OKBLUE + 'Getting .log files from', input_path)final_headers = [ 'Start Time', 'epoch', 'Host Name', 'Db Alias', 'Database', 'Db Host', 'Db Host IP', 'IP Port', 'Latency (us)']#read in files via list comprehensioncontent = [pd.read_csv(f,usecols = final_headers, sep='[;]',engine='python') for f in stock_files]print(bcolors.OKBLUE + 'Reading files')#combine files into one dataframecombo = pd.concat(content,ignore_index = True)print(bcolors.OKBLUE + 'Combining files')#drop duplicatescombo = combo.drop_duplicates()#combo = combo.drop_duplicates(final_headers, keep=False)print(bcolors.OKBLUE + 'Dropping duplicates')#write to csv:combo.to_csv(output_path + output_name, index = False)print(bcolors.OKGREEN + 'Merged file output to', output_path, 'as', output_name)
2 回答
交互式愛情
TA貢獻(xiàn)1712條經(jīng)驗(yàn) 獲得超3個贊
def func(row):
if row['Host Name'] == "dpc01n1":
return 'dev_dom1'
#do your Host Alias generate logic here,and return
combo["Host Alias"]=combo.apply(func, axis=1)
DataFrame.apply 接受一個函數(shù)來生成一個新的 Series 或 DataFrame
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html
jeck貓
TA貢獻(xiàn)1909條經(jīng)驗(yàn) 獲得超7個贊
像這樣的東西應(yīng)該工作：
import pandas as pd
combo = pd.DataFrame({
'Start Time' : [1,2,3],
'epoch' : [1,2,3],
'Host Name': ['dpc01n1','dpc02n1','dpc00103n1'],
'Db Alias' : [1,2,3],
'Database' : [1,2,3],
'Db Host' : [1,2,3],
'Db Host IP' : [1,2,3],
'IP Port' : [1,2,3],
'Latency (us)' : [1,2,3],
})
h_num = combo['Host Name'].str.lstrip('dpc0').str[:-2]
combo['Host Alias'] = 'dev_dom' + h_num
print(combo)
它假定所有'Host Name's 不以任何其他開頭，'dpc'并且不需要兩個尾隨字符 like 'n1'。python教程中的示例
評論中提出的后續(xù)問題：
它假定我合并的 csv 文件已經(jīng)有主機(jī)別名，但它不會導(dǎo)致錯誤：發(fā)生異常：ValueError Usecols 與列不匹配，列預(yù)期但未找到：['Host Alias'] File "D:\OneDrive \python\merger.py", line 42, in content = [pd.read_csv(f,usecols = combo_headers, sep='[;]',engine='python') 除了 dpc，我還有 tpc。我該如何添加呢？– 樹干
str.lstrip無論順序如何，都會刪除參數(shù)中提供的所有字符。只需添加一個't'：
h_num = combo['Host Name'].str.lstrip('tdpc0').str[:-2]至于：
它假定我合并的 csv 文件已經(jīng)有主機(jī)別名
我不確定你的意思。當(dāng)你這樣做
combo['Host Alias'] = 'dev_dom' + h_num
如果該列尚不存在，'Host Alias'則將在 中創(chuàng)建該列。pandas.DataFrame如果確實(shí)存在，則該列將被操作返回的新數(shù)據(jù)替換。然后，您可以使用pandas.DataFrame.to_csv將此 DataFrame 保存到 .csv 文件。
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