仅将不同的数据从一个.csv附加到另一个.csv

Question

I have managed to use Python with the speedtest-cli package to run a speedtest of my Internet speed. I run this every 15 min and append the results to a .csv file I call "speedtest.csv". I then have this .csv file emailed to me every 12 hours, which is a lot of data.

I am only interested in keeping the rows of data that return less than 13mbps Download speed. Using the following code, I am able to filter for this data and append it to a second .csv file I call speedtestfilteronly.csv .

import pandas as pd
df = pd.read_csv('c:\speedtest.csv', header=0)
df = df[df['Download'].map(lambda x: x < 13000000.0,)]
df.to_csv('c:\speedtestfilteronly.csv', mode='a', header=False)

The problem now is it appends all the rows that match my filter criteria every time I run this code. So if I run this code 4 times, I receive the same 4 sets of appended data in the "speedtestfilteronly.csv" file.

I am looking to only append unlike rows from speedtest.csv to speedtestfilteronly.csv.

How can I achieve this?

I have got the following code to work, except the only thing it is not doing is filtering the results to < 13000000.0 mb/s: Any other ideas?

import pandas as pd

df = pd.read_csv('c:\speedtest.csv', header=0)  
df = df[df['Download'].map(lambda x: x < 13000000.0,)]

history_df = pd.read_csv('c:\speedtest.csv')
master_df = pd.concat([history_df, df], axis=0)
new_master_df = master_df.drop_duplicates(keep="first")
new_master_df.to_csv('c:\emailspeedtest.csv', header=None, index=False)

Answer 1

There's a few different way you could approach this, one would be to read in your filtered dataset, append the new one in memory and then drop duplicates like this:

import pandas as pd

df = pd.read_csv('c:\speedtest.csv', header=0)
df = df[df['Download'].map(lambda x: x < 13000000.0,)]

history_df = pd.read_csv('c:\speedtestfilteronly.csv', header=None)
master_df = pd.concat([history_df, df], axis=0)
new_master_df = master_df.drop_duplicates(keep="first")
new_master_df.to_csv('c:\speedtestfilteronly.csv', header=None, index=False)