python读取csv文件中数据_python读取.csv文件中的数据

python 读取.csv文件中数据的库有两个，一个是csv库，一个是pandas库。

调用读取指令读取数据后得到一个csv对象，想要用numpy等库处理时候，需要对其进行转型。

csv读取

import os

import csv

import matplotlib.pyplot as plt

import numpy as np

data_sourse_dir = "G:\\project\\"

# 遍历数据结果下的所有文件

testids = os.listdir(data_sourse_dir)

fig = plt.figure(1)

legend_name1 = list()

for testid in testids:

if "target_name1" in testid:

real_data_dir = data_sourse_dir + testid + "\\"

testids2 = os.listdir(real_data_dir)

for testid2 in testids2:

if "agcBigScaleStatisticTable" in testid2:

ful_data_dir = real_data_dir + testid2

data_file = open(ful_data_dir,'r')

data = csv.reader(data_file)

counter_max_value = [row[20] for row in data]

counter_max_value = list(map(int,counter_max_value))

plt.plot(counter_max_value)

legend_name1.append(testid)

plt.legend(legend_name1,loc = "upper right")

fig = plt.figure(2)

legend_name2 = []

for testid in testids:

if "target_name2" in testid:

real_data_dir = data_sourse_dir + testid + "\\"

testids2 = os.listdir(real_data_dir)

for testid2 in testids2:

if "agcBigScaleStatisticTable" in testid2:

ful_data_dir = real_data_dir + testid2

data_file = open(ful_data_dir,'r')

data = csv.reader(data_file)

counter_max_value = [row[20] for row in data]

counter_max_value = list(map(int,counter_max_value))

plt.plot(counter_max_value)

legend_name2.append(testid)

plt.legend(legend_name2,loc = "upper right")

fig = plt.figure(3)

legend_name3 = []

for testid in testids:

if "target_name3" in testid:

real_data_dir = data_sourse_dir + testid + "\\"

testids2 = os.listdir(real_data_dir)

for testid2 in testids2:

if "agcBigScaleStatisticTable" in testid2:

ful_data_dir = real_data_dir + testid2

data_file = open(ful_data_dir,'r')

data = csv.reader(data_file)

counter_max_value = [row[20] for row in data]

counter_max_value = list(map(int,counter_max_value))

plt.plot(counter_max_value)

legend_name3.append(testid)

plt.legend(legend_name3,loc = "upper right")

plt.show()

pandas 读取

import pandas as pd

from matplotlib import pyplot as plt

agc_param = pd.read_csv(unit_test_output_dir + test_csv, index_col=None, dtype={'voiceProb': 'float64', 'energyProb': 'float64', 'snr': 'float64', 'firstStageGain': 'float64'})

agc_param.to_numpy()

key = 'target_key_to_be_ploted'

plt.plot(agc_param[key])

plt.show()