Reputation: 199
I have CSV, which is in a list. Example:
[[R2C1,R01,API_1,801,API_TEST01],
[R2C1,R01,API_1,802,API_TEST02],
[R2C1,R01,API_1,801,API_TEST03]]
Like to find out the all the unique in i[3]
and count them.
results:
[{num: 801, count: 2}, {num: 802, count: 1}]
so that I can call dict
key for another test.
Code:
for row in data[1:]:
vnum = row[3]
ipcount.append({"num":vnum,"count": count})
if row[3] not in ipcount:
ipcount.append({"num":vlan})
Upvotes: 5
Views: 8342
Reputation: 4018
here a pure pandas
approach without any loops
import pandas as pd
# define path to data
PATH = u'path\to\data.csv'
# create panda datafrmae
df = pd.read_csv(PATH, usecols = [0,1,2,3], header = 0, names = ['a', 'b', 'c','num'])
# Add count to column of interest
df['count'] = df.groupby('num')['num'].transform('count')
# only keep unique values in column of interest
df.drop_duplicates(subset=['num'], inplace = True)
# create dict from bowth columns
your_output = dict(zip(df.num, df.count))
Upvotes: 0
Reputation: 7045
If you use the pandas
library:
import pandas as pd
# Open your file using pd.read_csv() or from your list of lists
df = pd.DataFrame([['R2C1','R01','API_1',801,'API_TEST01'],
['R2C1','R01','API_1',802,'API_TEST02'],
['R2C1','R01','API_1',801,'API_TEST03']])
print(df)
0 1 2 3 4
0 R2C1 R01 API_1 801 API_TEST01
1 R2C1 R01 API_1 802 API_TEST02
2 R2C1 R01 API_1 801 API_TEST03
Here you can use .value_counts()
to get the number of each value in column 3
, then using a dictionary comprehension transform this into the form you need:
[{'num': k, 'count': v} for k, v in dict(df[3].value_counts()).items()]
[{'num': 801, 'count': 2}, {'num': 802, 'count': 1}]
Upvotes: 2
Reputation: 48357
You can do this using a dictionary in order to group list items by num
element. The last step is using a list comprehension in order to achieve your desired result.
dict = {}
for elem in data:
if elem[3] not in dict:
dict[elem[3]] = 0
dict[elem[3]] = dict[elem[3]] + 1
final_list = [{'num' : elem, 'count': dict[elem]} for elem in dict]
Output
[{'num': 801, 'count': 2}, {'num': 802, 'count': 1}]
Upvotes: 1