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data_analicys.py
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import csv
import numpy as np
with open('/data1/luojingzhou/datasets/gaiic_dataset/semi_train.csv', newline='') as csvfile:
# 读取csv文件
reader = csv.reader(csvfile)
# 创建两个空列表，用于存储每一列的数据
column1 = []
column2 = []
column3 = []
# 遍历每一行数据，将每一列的数据添加到对应的列表中
max_input_L = 0
max_output_L = 0
max_L = 0
min_input_L = 10000
min_output_L = 10000
L = 0
count = 0
for row in reader:
_, col1, col2, col3 = row
a = []
b = []
c = []
a.extend(map(int, col1.split()))
b.extend(map(int, col2.split()))
c.extend(map(int, col3.split()))
if len(c)==0:
count += 1
print(col3=='')
print(count)
# L += len(list(a))+len(list(b))
# if max_input_L<len(list(c)):
# max_input_L = len(list(c))
# # if max_output_L<len(list(b)):
# # max_output_L = len(list(b))
# max_L = max(max_L,len(list(a))+len(list(c)))
# if min_input_L>len(list(c)):
# min_input_L = len(list(c))
# # if min_output_L>len(list(b)):
# # min_output_L = len(list(b))
# column1.extend(map(int, col1.split()))
# column2.extend(map(int, col2.split()))
# column3.extend(map(int, col3.split()))
# text = column1 + column2 +column3
# print(max_L,max_input_L,min_input_L)
# exit()
# with open('/data1/luojingzhou/datasets/gaiic_dataset/semi_train.csv', newline='') as csvfile:
# # 读取csv文件
# reader = csv.reader(csvfile)
# # 创建两个空列表，用于存储每一列的数据
# column1 = []
# column2 = []
# column3 = []
# # 遍历每一行数据，将每一列的数据添加到对应的列表中
# max_input_L = 0
# max_output_L = 0
# max_L = 0
# min_input_L = 10000
# min_output_L = 10000
# L = 0
# count = 0
# for row in reader:
# count += 1
# _, col1, col2, col3 = row
# a = []
# b = []
# c = []
# a.extend(map(int, col1.split()))
# b.extend(map(int, col2.split()))
# c.extend(map(int, col3.split()))
# L += len(list(a))+len(list(b))
# # if max_input_L<len(list(a)):
# # max_input_L = len(list(a))
# # if max_output_L<len(list(b)):
# # max_output_L = len(list(b))
# # max_L = max(max_L,len(list(a))+len(list(b)))
# # if min_input_L>len(list(a)):
# # min_input_L = len(list(a))
# # if min_output_L>len(list(b)):
# # min_output_L = len(list(b))
# column1.extend(map(int, col1.split()))
# column2.extend(map(int, col2.split()))
# column3.extend(map(int, col3.split()))
# text = column1 + column2 +column3
# # 打开csv文件
# with open('/data1/luojingzhou/datasets/gaiic_dataset/train.csv', newline='') as csvfile:
# # 读取csv文件
# reader = csv.reader(csvfile)
# # 创建两个空列表，用于存储每一列的数据
# column1 = []
# column2 = []
# # 遍历每一行数据，将每一列的数据添加到对应的列表中
# max_input_L = 0
# max_output_L = 0
# max_L = 0
# min_input_L = 10000
# min_output_L = 10000
# L = 0
# count = 0
# for row in reader:
# count += 1
# _, col1, col2 = row
# a = []
# b = []
# a.extend(map(int, col1.split()))
# b.extend(map(int, col2.split()))
# L += len(list(a))+len(list(b))
# if max_input_L<len(list(a)):
# max_input_L = len(list(a))
# if max_output_L<len(list(b)):
# max_output_L = len(list(b))
# max_L = max(max_L,len(list(a))+len(list(b)))
# if min_input_L>len(list(a)):
# min_input_L = len(list(a))
# if min_output_L>len(list(b)):
# min_output_L = len(list(b))
# column1.extend(map(int, col1.split()))
# column2.extend(map(int, col2.split()))
# text = column1 + column2
with open('/data1/luojingzhou/datasets/gaiic_dataset/preliminary_a_test.csv', newline='') as csvfile:
# 读取csv文件
reader = csv.reader(csvfile)
# 创建两个空列表，用于存储每一列的数据
column1 = []
# 遍历每一行数据，将每一列的数据添加到对应的列表中
for row in reader:
_, col1 = row
a = []
a.extend(map(int, col1.split()))
column1.extend(map(int, col1.split()))
text += column1
# 使用numpy计算最大值、最小值和平均值
max_val = np.max(text)
min_val = np.min(text)
avg_val = np.mean(text)
# 使用numpy统计数字分布
hist, bins = np.histogram(text, bins=range(min_val, max_val+2))
for i in range(len(hist)):
if hist[i]<10:
print(bins[i],bins[i+1])
print('数字分布统计：')
for i in range(len(hist)):
print(f'{bins[i]} - {bins[i+1]-1}: {hist[i]}')
# 打印最大值、最小值和平均值
print(max_val,min_val,avg_val)
print('max_input_L,max_output_L:',max_input_L,max_output_L)
print('min_input_L,min_output_L:',min_input_L,min_output_L)
#pred
with open('/data1/luojingzhou/projects/gaiic_hugging/pred.csv', newline='') as csvfile:
# 读取csv文件
reader = csv.reader(csvfile)
# 创建两个空列表，用于存储每一列的数据
column1 = []
# 遍历每一行数据，将每一列的数据添加到对应的列表中
for row in reader:
_, col1 = row
a = []
a.extend(map(int, col1.split()))
column1.extend(map(int, col1.split()))
text = column1
# 使用numpy计算最大值、最小值和平均值
max_val = np.max(text)
min_val = np.min(text)
avg_val = np.mean(text)
# 使用numpy统计数字分布
hist, bins = np.histogram(text, bins=range(min_val, max_val+2))
print('数字分布统计：')
for i in range(len(hist)):
print(f'{bins[i]} - {bins[i+1]-1}: {hist[i]}')
# 打印最大值、最小值和平均值
print('max_val,min_val,avg_val:',max_val,min_val,avg_val)