How to filter my CSV results using Python

Question

I have a csv file where i have columns as follows:

Source Rack  Switch Label/ID     Switch no  Switch Port    
    1            Hostname1        Switch1         1

with around 100 values in them. My goal is to filter the Label and see how many ports are used. Apart from that, get a count value of the number of ports used by the switch.

Using CSVreader i get the values in python but i am stuck trying to filter them. Please suggest a method to get this done.

Thanks!

import pandas as pd
import csv
import  numpy
import matplotlib

#import datetime
#import pandas.io.data


data_df = pd.read_csv('patchingwlan.csv',index_col = 1)
data_df.filter(items=['Hostname','Switch Port'])
print(data_df.head())

Answer 1

If I've understood correctly, you want something like this:

import pandas as pd
pd.set_option("display.width", 300)

# Test input data
df = pd.DataFrame({
    "label": ["hostname1", "hostname1", "hostname2", "hostname2"],
    "switch_no": ["Switch1", "Switch1", "Switch1", "Switch2"],
    "switch_port": [1, 1, 2, 3]
})
print df

# Count ports per label and ports per switch_no (unique and total, depending on what you want)
df["unique_ports_per_label"] = df.groupby("label")["switch_port"].transform("nunique")
df["ports_per_label"] = df.groupby("label")["switch_port"].transform(len)
df["unique_ports_per_switch"] = df.groupby("switch_no")["switch_port"].transform("nunique")
df["ports_per_switch"] = df.groupby("switch_no")["switch_port"].transform(len)
print df

Which results in:

       label switch_no  switch_port
0  hostname1   Switch1            1
1  hostname1   Switch1            1
2  hostname2   Switch1            2
3  hostname2   Switch2            3

After:

       label switch_no  switch_port  unique_ports_per_label  ports_per_label  unique_ports_per_switch  ports_per_switch
0  hostname1   Switch1            1                       1                2                        2                 3
1  hostname1   Switch1            1                       1                2                        2                 3
2  hostname2   Switch1            2                       2                2                        2                 3
3  hostname2   Switch2            3                       2                2                        1                 1