计算 csv 文件中出现的次数

Question

I want to be able to make a bar chart with the number of occurrences of a certain room (stored in a csv file). the number of rooms is not defined in the beginning.

this is the data stored in the csv file:

this is the type of graph i want to show, but with the code i currently have it doesn't show the number of occurrences.

what can i do to solve this problem?

this is my code so far.

with open('calls.csv') as File:  
    plots = csv.reader(File, delimiter = ',')

   for row in plots:
        if (row[0] not in x):
            x.append(row[0])
       numberOfRooms = len(x)

    for i in range(numberOfRooms):
        occurence = 0
        for row in plots:
            if(x[i] == row[0]):
                occurence += 1
        y.append(occurence)

plt.bar(x,y, width = 0.7, label="Number of calls")
plt.xlabel('room')
plt.ylabel('number of calls')
plt.title('Number of calls per room')
plt.legend()
plt.show()

Answer 1

Since you tagged Pandas, you can do:

# read dataframe from csv
df = pd.read_csv('calls.csv')

# count the values in the first column
counts = df.iloc[:,0].value_counts()

# plot the count
counts.plot.bar()

That said, you can certainly use csv package, but you should probably use a different data structure, eg dictionary:

with open('calls.csv') as File:  
    data = csv.reader(File, delimiter = ',')

    counts = {}
    
    # loop through data
    for row in data:
        room = row[0]

        # initiate if room is first seen
        if room not in counts: counts[room] = 0

        # increase the count
        counts[room] += 1
    
# plot the counts
plt.bar(list(counts.keys()), list(counts.values()) )

Answer 2

For a task like this, using only the "built-ins", I'd use a dictionary to accumulate the data

data = {}
with open('calls.csv') as File:  
    plots = csv.reader(File, delimiter = ',')
    for row in plots:
        # increments the counter of occurrences, 
        # if the key is not already in there, .get() will return the 0 as a default
        data[row[0]] = data.get(row[0],0) + 1
# at this point we have processed the whole file, so let's prepare data for plotting
# we take the keys of the dictionary and sort them for the x axis
x = list(data.keys())
x.sort()
# the we take the values, the count of occurrences, in the same order
y = [data[i] for i in x]
# then just ... plot it. 
plt.bar(x, y, width = 0.7, label="Number of calls")
plt.xlabel('room')
plt.ylabel('number of calls')
plt.title('Number of calls per room')
plt.legend()
plt.show()

Answer 3

Without pandas , you can save the number of calls per rooms in a dict and use this to plot:

import csv
import matplotlib.pyplot as plt

rooms = dict()
with open("calls.csv") as infile:
    csvreader = csv.reader(infile)
    
    for row in csvreader:
        if row[0] not in rooms:
            rooms[row[0]] = 0
        rooms[row[0]] += 1

plt.bar(rooms.keys(), rooms.values(), width=0.7)
plt.xlabel("room")
plt.ylabel("number of calls")
plt.title("Number of calls per room")

Output: