<commit_before>from pandas import read_csv
import pandas as pd
import numpy as np
<commit_msg>MissData<commit_after>from pandas import read_csv
import numpy as np
header= ['sequentialNumber','xAcceleration','yAcceleration','zAcceleration','lable']
num = 1
#allData=read_csv('data/1.csv', header=None)
while(num < 16):
#  #   dataset = read_csv('data/%d.csv' % (num), header=None)
#  #   allData = allData.append(dataset,ignore_index=False,verify_integrity=False)
    dataset = read_csv('data/%d.csv' % (num) , names=header)
    boolData = dataset.isnull()
    for idx in header:
       print(boolData.loc[boolData[idx] == True])
    num += 1
    # print(dataset.describe())
 #print(allData)

 #define the function for  delete rows with 0 Labels
 # @input: Pandas Dataframe, value of lable to delet
 # @output: Array of int without lable 0
def zeroDet( dataset, value ):
    num = []
    num=(dataset.loc[dataset['lable'] == value].index.values)
    dataClean=(dataset.drop(num))
    dataClean = dataClean.as_matrix()
    dataClean = dataClean.astype(np.int)
    return dataClean;

dataset=read_csv('data/1.csv', names=header)
dataArray=zeroDet(dataset,0)
print(dataArray)

{'fraction_non_alphanumeric': 0.13737201365187712, 'fraction_numerical': 0.007679180887372013, 'mean_word_length': 4.865, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '2790170', 'n_tokens_mistral': 399, 'n_tokens_neox': 384, 'n_words': 92}