drop_duplicates 在 pandas 中不起作用?
问题描述
我的代码的目的是导入 2 个 Excel 文件，比较它们，然后将差异打印到一个新的 Excel 文件中.
The purpose of my code is to import 2 Excel files, compare them, and print out the differences to a new Excel file.
但是，在连接所有数据并使用 drop_duplicates 函数后，代码会被控制台接受.但是，当打印到新的 excel 文件时，当天仍会保留重复项.
However, after concatenating all the data, and using the drop_duplicates function, the code is accepted by the console. But, when printed to the new excel file, duplicates still remain within the day.
我错过了什么吗?drop_duplicates 函数是否无效?
Am I missing something? Is something nullifying the drop_duplicates function?
我的代码如下:
import datetime
import xlrd
import pandas as pd
#identify excel file paths
filepath = r"excel filepath"
filepath2 = r"excel filepath2"
#read relevant columns from the excel files
df1 = pd.read_excel(filepath, sheetname="Sheet1", parse_cols= "B, D, G, O")
df2 = pd.read_excel(filepath2, sheetname="Sheet1", parse_cols= "B, D, F, J")
#merge the columns from both excel files into one column each respectively
df4 = df1["Exchange Code"] + df1["Product Type"] + df1["Product Description"] + df1["Quantity"].apply(str)
df5 = df2["Exchange"] + df2["Product Type"] + df2["Product Description"] + df2["Quantity"].apply(str)
#concatenate both columns from each excel file, to make one big column containing all the data
df = pd.concat([df4, df5])
#remove all whitespace from each row of the column of data
df=df.str.strip()
df=["".join(x.split()) for x in df]
#convert the data to a dataframe from a series
df = pd.DataFrame({'Value': df})
#remove any duplicates
df.drop_duplicates(subset=None, keep="first", inplace=False)
#print to the console just as a visual aid
print(df)
#print the erroneous entries to an excel file
df.to_excel("Comparison19.xls")
解决方案
你有 inplace=False 所以你没有修改 df.你想要一个
You've got inplace=False so you're not modifying df. You want either
df.drop_duplicates(subset=None, keep="first", inplace=True)
或
df = df.drop_duplicates(subset=None, keep="first", inplace=False)
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