将所有数组保存到csv中,而不是仅保存最后一组数组

时间:2018-11-01 02:55:41

标签: python pandas csv numpy dataframe

我在获取数据以正确保存到csv时遇到问题。我在x [zpeaks]中有几组数组,但是当我保存数据时,它只保存最后一个数组,而不是全部。

例如,假设我的x [zpeaks]包含[1,2,1],[1,4,1],[1,3,5]。但是当我想将所有数组保存在csv文件中时,它只会保存最后一个数组为[1,3,5]。

import matplotlib.pyplot as plt
import numpy as np
from scipy.signal import find_peaks
import pdb
import pandas as pd

t = []
z = []
y = []
x = []

with open("Data1r2.txt", 'r') as f:
    for line in f:
        parts = line.split(", ")
        x.append(float(parts[0][2:]))
        y.append(float(parts[1][2:]))
        z.append(float(parts[2][2:]))
        t.append(float(parts[3][2:]))

zz = np.array(z)
tt = np.array(t)
zminvalue = np.min(zz)
zzz = zz - zminvalue
zpeaks, _ = find_peaks(zzz)

for i in range(len(zpeaks)-1):
            print(z[zpeaks[i]:zpeaks[i+1]])
            a = (x[zpeaks[i]:zpeaks[i+1]])
            b = (y[zpeaks[i]:zpeaks[i+1]])
            c = (z[zpeaks[i]:zpeaks[i+1]])
    pd.concat([pd.DataFrame(a),pd.DataFrame(b), pd.DataFrame(c)], axis=1).to_csv('Diff.csv', mode='w')

我的data.txt

X:-241, Y:-31, Z:17, T:73823
X:-241, Y:-31, Z:17, T:73952
X:-240, Y:-30, Z:26, T:74073
X:-240, Y:-30, Z:26, T:74191
X:-240, Y:-30, Z:26, T:74312
X:-240, Y:-32, Z:39, T:74432
X:-240, Y:-32, Z:39, T:74549
X:-240, Y:-32, Z:39, T:74668
X:-239, Y:-21, Z:12, T:74785
X:-239, Y:-21, Z:12, T:74904
X:-239, Y:-21, Z:12, T:75022
X:-246, Y:15, Z:18, T:75142
X:-246, Y:15, Z:18, T:75260
X:-246, Y:15, Z:18, T:75378
X:-250, Y:19, Z:14, T:75498
X:-250, Y:19, Z:14, T:75615
X:-250, Y:19, Z:14, T:75732
X:-239, Y:-5, Z:27, T:75854
X:-239, Y:-5, Z:27, T:75972
X:-239, Y:-5, Z:27, T:76102
X:-236, Y:-19, Z:46, T:76240
X:-236, Y:-19, Z:46, T:76369
X:-236, Y:-19, Z:46, T:76489
X:-235, Y:-14, Z:32, T:76610
X:-235, Y:-14, Z:32, T:76727
X:-235, Y:-14, Z:32, T:76845
X:-244, Y:-16, Z:22, T:76963
X:-244, Y:-16, Z:22, T:77081
X:-244, Y:-16, Z:22, T:77201
X:-220, Y:-25, Z:-3, T:77346
X:-220, Y:-25, Z:-3, T:77464
X:-220, Y:-25, Z:-3, T:77580
X:-229, Y:24, Z:2, T:77699
X:-229, Y:24, Z:2, T:77814
X:-229, Y:24, Z:2, T:77934
X:-248, Y:-20, Z:0, T:78052
X:-248, Y:-20, Z:0, T:78171
X:-248, Y:-20, Z:0, T:78288
X:-242, Y:-15, Z:-35, T:78515
X:-242, Y:-15, Z:-35, T:78630
X:-242, Y:-15, Z:-35, T:78747
X:-235, Y:-12, Z:-63, T:78865
X:-235, Y:-12, Z:-63, T:78982
X:-235, Y:-12, Z:-63, T:79102
X:-226, Y:-35, Z:-145, T:79221
X:-226, Y:-35, Z:-145, T:79340
X:-226, Y:-35, Z:-145, T:79461
X:-205, Y:-47, Z:-156, T:79582
X:-205, Y:-47, Z:-156, T:79702
X:-205, Y:-47, Z:-156, T:79821
X:-208, Y:-39, Z:-149, T:79940
X:-208, Y:-39, Z:-149, T:80061
X:-208, Y:-39, Z:-149, T:80181
X:-235, Y:-16, Z:-99, T:80304
X:-235, Y:-16, Z:-99, T:80432
X:-235, Y:-16, Z:-99, T:80657
X:-247, Y:-10, Z:12, T:80774
X:-247, Y:-10, Z:12, T:80890
X:-247, Y:-10, Z:12, T:81008
X:-242, Y:-1, Z:2, T:81127
X:-242, Y:-1, Z:2, T:81246
X:-242, Y:-1, Z:2, T:81363
X:-239, Y:-8, Z:15, T:81483
X:-239, Y:-8, Z:15, T:81600
X:-239, Y:-8, Z:15, T:81720
X:-241, Y:-13, Z:-11, T:81841
X:-241, Y:-13, Z:-11, T:81958
X:-241, Y:-13, Z:-11, T:82076
X:-242, Y:-5, Z:-37, T:82198
X:-242, Y:-5, Z:-37, T:82315
X:-242, Y:-5, Z:-37, T:82435
X:-215, Y:-43, Z:-128, T:82554
X:-215, Y:-43, Z:-128, T:82699
X:-215, Y:-43, Z:-128, T:82829
X:-207, Y:-48, Z:-153, T:82952
X:-207, Y:-48, Z:-153, T:83072
X:-207, Y:-48, Z:-153, T:83191
X:-198, Y:-37, Z:-166, T:83315
X:-198, Y:-37, Z:-166, T:83453
X:-198, Y:-37, Z:-166, T:83572
X:-218, Y:-33, Z:-134, T:83694
X:-218, Y:-33, Z:-134, T:83812
X:-218, Y:-33, Z:-134, T:83932
X:-228, Y:-15, Z:-80, T:84047
X:-228, Y:-15, Z:-80, T:84166
X:-228, Y:-15, Z:-80, T:84288
X:-243, Y:-8, Z:-4, T:84407
X:-243, Y:-8, Z:-4, T:84524
X:-243, Y:-8, Z:-4, T:84640
X:-238, Y:-4, Z:2, T:84756
X:-238, Y:-4, Z:2, T:84872
X:-238, Y:-4, Z:2, T:84994
X:-252, Y:-7, Z:-16, T:85136
X:-252, Y:-7, Z:-16, T:85265
X:-252, Y:-7, Z:-16, T:85385
X:-243, Y:-3, Z:-28, T:85504
X:-243, Y:-3, Z:-28, T:85618
X:-243, Y:-3, Z:-28, T:85739
X:-241, Y:-3, Z:-48, T:85858
X:-241, Y:-3, Z:-48, T:85975
X:-241, Y:-3, Z:-48, T:86094
X:-231, Y:-15, Z:-112, T:86216
X:-231, Y:-15, Z:-112, T:86334
X:-231, Y:-15, Z:-112, T:86453
X:-210, Y:-43, Z:-150, T:86573
X:-210, Y:-43, Z:-150, T:86691
X:-210, Y:-43, Z:-150, T:86811
X:-193, Y:-58, Z:-169, T:86933
X:-193, Y:-58, Z:-169, T:87051
X:-193, Y:-58, Z:-169, T:87171
X:-182, Y:-27, Z:-179, T:87305
X:-182, Y:-27, Z:-179, T:87435
X:-182, Y:-27, Z:-179, T:87566
X:-212, Y:-19, Z:-136, T:87686
X:-212, Y:-19, Z:-136, T:87803
X:-212, Y:-19, Z:-136, T:87920
X:-233, Y:-25, Z:-83, T:88040
X:-233, Y:-25, Z:-83, T:88160
X:-233, Y:-25, Z:-83, T:88278
X:-243, Y:-16, Z:-31, T:88396
X:-243, Y:-16, Z:-31, T:88510
X:-243, Y:-16, Z:-31, T:88625
X:-244, Y:-13, Z:-27, T:88744
X:-244, Y:-13, Z:-27, T:88860
X:-244, Y:-13, Z:-27, T:88978
X:-243, Y:-15, Z:-51, T:89099
X:-243, Y:-15, Z:-51, T:89218
X:-243, Y:-15, Z:-51, T:89338
X:-228, Y:-27, Z:-78, T:89472
X:-228, Y:-27, Z:-78, T:89601
X:-228, Y:-27, Z:-78, T:89746
X:-223, Y:-24, Z:-114, T:89876
X:-223, Y:-24, Z:-114, T:89995
X:-223, Y:-24, Z:-114, T:90115
X:-205, Y:-42, Z:-141, T:90236
X:-205, Y:-42, Z:-141, T:90354
X:-205, Y:-42, Z:-141, T:90474
X:-199, Y:-67, Z:-153, T:90595
X:-199, Y:-67, Z:-153, T:90713
X:-199, Y:-67, Z:-153, T:90833
X:-202, Y:-53, Z:-152, T:90951
X:-202, Y:-53, Z:-152, T:91069
X:-202, Y:-53, Z:-152, T:91191
X:-224, Y:-41, Z:-135, T:91312
X:-224, Y:-41, Z:-135, T:91431
X:-224, Y:-41, Z:-135, T:91549
X:-229, Y:-29, Z:-91, T:91669
X:-229, Y:-29, Z:-91, T:91789
X:-229, Y:-29, Z:-91, T:91923
X:-242, Y:-8, Z:-2, T:92066
X:-242, Y:-8, Z:-2, T:92184
X:-242, Y:-8, Z:-2, T:92302
X:-233, Y:-12, Z:-5, T:92420
X:-233, Y:-12, Z:-5, T:92534
X:-233, Y:-12, Z:-5, T:92654
X:-246, Y:-1, Z:-4, T:92773
X:-246, Y:-1, Z:-4, T:92892
X:-246, Y:-1, Z:-4, T:93010
X:-242, Y:-9, Z:-23, T:93130
X:-242, Y:-9, Z:-23, T:93251
X:-242, Y:-9, Z:-23, T:93370
X:-237, Y:-19, Z:-46, T:93491
X:-237, Y:-19, Z:-46, T:93608
X:-237, Y:-19, Z:-46, T:93727
X:-213, Y:-23, Z:-95, T:93849
X:-213, Y:-23, Z:-95, T:93966
X:-213, Y:-23, Z:-95, T:94112
X:-207, Y:-36, Z:-151, T:94241
X:-207, Y:-36, Z:-151, T:94359
X:-207, Y:-36, Z:-151, T:94480
X:-199, Y:-49, Z:-162, T:94600
X:-199, Y:-49, Z:-162, T:94721
X:-199, Y:-49, Z:-162, T:94840
X:-203, Y:-36, Z:-146, T:94961
X:-203, Y:-36, Z:-146, T:95082
X:-203, Y:-36, Z:-146, T:95202
X:-222, Y:-28, Z:-124, T:95324
X:-222, Y:-28, Z:-124, T:95439
X:-222, Y:-28, Z:-124, T:95583
X:-244, Y:2, Z:-53, T:95700
X:-244, Y:2, Z:-53, T:95817
X:-244, Y:2, Z:-53, T:95935
X:-237, Y:-5, Z:-9, T:96055
X:-237, Y:-5, Z:-9, T:96171
X:-237, Y:-5, Z:-9, T:96301
X:-239, Y:-2, Z:1, T:96439
X:-239, Y:-2, Z:1, T:96568
X:-239, Y:-2, Z:1, T:96685
X:-243, Y:-4, Z:2, T:96805
X:-243, Y:-4, Z:2, T:96919
X:-243, Y:-4, Z:2, T:97037
X:-246, Y:-3, Z:-16, T:97159
X:-246, Y:-3, Z:-16, T:97276
X:-246, Y:-3, Z:-16, T:97395
X:-239, Y:-8, Z:-42, T:97513
X:-239, Y:-8, Z:-42, T:97631
X:-239, Y:-8, Z:-42, T:97752
X:-221, Y:-10, Z:-115, T:97871
X:-221, Y:-10, Z:-115, T:97990
X:-221, Y:-10, Z:-115, T:98109
X:-219, Y:-25, Z:-145, T:98230
X:-219, Y:-25, Z:-145, T:98350
X:-219, Y:-25, Z:-145, T:98468
X:-202, Y:-31, Z:-172, T:98589
X:-202, Y:-31, Z:-172, T:98736
X:-202, Y:-31, Z:-172, T:98865
X:-214, Y:-34, Z:-144, T:98985
X:-214, Y:-34, Z:-144, T:99101
X:-214, Y:-34, Z:-144, T:99223
X:-224, Y:-24, Z:-116, T:99342
X:-224, Y:-24, Z:-116, T:99460
X:-224, Y:-24, Z:-116, T:99579
X:-232, Y:2, Z:-50, T:99699
X:-232, Y:2, Z:-50, T:99818
X:-232, Y:2, Z:-50, T:99936
X:-241, Y:-4, Z:-22, T:100056
X:-241, Y:-4, Z:-22, T:100175
X:-241, Y:-4, Z:-22, T:100293
X:-240, Y:4, Z:-2, T:100414
X:-240, Y:4, Z:-2, T:100532
X:-240, Y:4, Z:-2, T:100648
X:-241, Y:3, Z:1, T:100768
X:-241, Y:3, Z:1, T:100895
X:-241, Y:3, Z:1, T:101029
X:-243, Y:1, Z:-16, T:101160
X:-243, Y:1, Z:-16, T:101278
X:-243, Y:1, Z:-16, T:101399
X:-239, Y:-2, Z:-36, T:101518
X:-239, Y:-2, Z:-36, T:101661
X:-239, Y:-2, Z:-36, T:101780
X:-228, Y:-12, Z:-71, T:101901
X:-228, Y:-12, Z:-71, T:102019
X:-228, Y:-12, Z:-71, T:102138
X:-224, Y:-23, Z:-118, T:102260
X:-224, Y:-23, Z:-118, T:102378
X:-224, Y:-23, Z:-118, T:102498
X:-209, Y:-2, Z:-161, T:102617
X:-209, Y:-2, Z:-161, T:102735
X:-209, Y:-2, Z:-161, T:102855
X:-206, Y:-3, Z:-150, T:102974
X:-206, Y:-3, Z:-150, T:103088
X:-206, Y:-3, Z:-150, T:103216
X:-218, Y:0, Z:-142, T:103355
X:-218, Y:0, Z:-142, T:103469
X:-218, Y:0, Z:-142, T:103581
X:-226, Y:-17, Z:-118, T:103700
X:-226, Y:-17, Z:-118, T:103814
X:-226, Y:-17, Z:-118, T:103931
X:-242, Y:4, Z:-40, T:104054
X:-242, Y:4, Z:-40, T:104171
X:-242, Y:4, Z:-40, T:104292
X:-242, Y:4, Z:-22, T:104410
X:-242, Y:4, Z:-22, T:104523
X:-242, Y:4, Z:-22, T:104642
X:-240, Y:5, Z:-3, T:104762
X:-240, Y:5, Z:-3, T:104879
X:-240, Y:5, Z:-3, T:104993
X:-244, Y:-2, Z:-6, T:105111
X:-244, Y:-2, Z:-6, T:105231
X:-244, Y:-2, Z:-6, T:105361
X:-244, Y:1, Z:-10, T:105497
X:-244, Y:1, Z:-10, T:105623
X:-244, Y:1, Z:-10, T:105744
X:-244, Y:-4, Z:-34, T:105865
X:-244, Y:-4, Z:-34, T:105981
X:-244, Y:-4, Z:-34, T:106101
X:-231, Y:-1, Z:-63, T:106222
X:-231, Y:-1, Z:-63, T:106341
X:-231, Y:-1, Z:-63, T:106462
X:-222, Y:-11, Z:-116, T:106580
X:-222, Y:-11, Z:-116, T:106698
X:-222, Y:-11, Z:-116, T:106818
X:-219, Y:-15, Z:-144, T:106938
X:-219, Y:-15, Z:-144, T:107058
X:-219, Y:-15, Z:-144, T:107174
X:-204, Y:-6, Z:-150, T:107297
X:-204, Y:-6, Z:-150, T:107410
X:-204, Y:-6, Z:-150, T:107528
X:-196, Y:-5, Z:-163, T:107665
X:-196, Y:-5, Z:-163, T:107802
X:-196, Y:-5, Z:-163, T:107935
X:-214, Y:-2, Z:-153, T:108066
X:-214, Y:-2, Z:-153, T:108186
X:-214, Y:-2, Z:-153, T:108306
X:-223, Y:-12, Z:-123, T:108422
X:-223, Y:-12, Z:-123, T:108544
X:-223, Y:-12, Z:-123, T:108661
X:-230, Y:7, Z:-52, T:108783
X:-230, Y:7, Z:-52, T:108900
X:-230, Y:7, Z:-52, T:109019
X:-241, Y:9, Z:-25, T:109139
X:-241, Y:9, Z:-25, T:109258
X:-241, Y:9, Z:-25, T:109375
X:-245, Y:4, Z:-12, T:109496
X:-245, Y:4, Z:-12, T:109612
X:-245, Y:4, Z:-12, T:109732
X:-242, Y:3, Z:-6, T:109852
X:-242, Y:3, Z:-6, T:109968
X:-242, Y:3, Z:-6, T:110098
X:-239, Y:-4, Z:-35, T:110243
X:-239, Y:-4, Z:-35, T:110362
X:-239, Y:-4, Z:-35, T:110484
X:-235, Y:6, Z:-65, T:110606
X:-235, Y:6, Z:-65, T:110722
X:-235, Y:6, Z:-65, T:110840
X:-215, Y:-14, Z:-117, T:110962
X:-215, Y:-14, Z:-117, T:111081
X:-215, Y:-14, Z:-117, T:111204
X:-224, Y:7, Z:-146, T:111324
X:-224, Y:7, Z:-146, T:111441
X:-224, Y:7, Z:-146, T:111561
X:-209, Y:-6, Z:-149, T:111679
X:-209, Y:-6, Z:-149, T:111799
X:-209, Y:-6, Z:-149, T:111919
X:-219, Y:-8, Z:-140, T:112038
X:-219, Y:-8, Z:-140, T:112157
X:-219, Y:-8, Z:-140, T:112274
X:-226, Y:-3, Z:-116, T:112405
X:-226, Y:-3, Z:-116, T:112540
X:-226, Y:-3, Z:-116, T:112669
X:-233, Y:2, Z:-76, T:112792
X:-233, Y:2, Z:-76, T:112909
X:-233, Y:2, Z:-76, T:113028
X:-237, Y:7, Z:-35, T:113148
X:-237, Y:7, Z:-35, T:113266
X:-237, Y:7, Z:-35, T:113386
X:-242, Y:5, Z:-15, T:113504
X:-242, Y:5, Z:-15, T:113624
X:-242, Y:5, Z:-15, T:113764
X:-244, Y:5, Z:-3, T:113884
X:-244, Y:5, Z:-3, T:113999
X:-244, Y:5, Z:-3, T:114118
X:-242, Y:3, Z:-7, T:114239
X:-242, Y:3, Z:-7, T:114357
X:-242, Y:3, Z:-7, T:114473
X:-241, Y:0, Z:-30, T:114595
X:-241, Y:0, Z:-30, T:114720
X:-241, Y:0, Z:-30, T:114867
X:-227, Y:-13, Z:-95, T:114989
X:-227, Y:-13, Z:-95, T:115104
X:-227, Y:-13, Z:-95, T:115224
X:-212, Y:-5, Z:-114, T:115343
X:-212, Y:-5, Z:-114, T:115462
X:-212, Y:-5, Z:-114, T:115579
X:-215, Y:-6, Z:-145, T:115701
X:-215, Y:-6, Z:-145, T:115819
X:-215, Y:-6, Z:-145, T:115937
X:-210, Y:5, Z:-142, T:116059
X:-210, Y:5, Z:-142, T:116176
X:-210, Y:5, Z:-142, T:116296
X:-222, Y:-19, Z:-145, T:116415
X:-222, Y:-19, Z:-145, T:116534
X:-222, Y:-19, Z:-145, T:116655
X:-231, Y:6, Z:-119, T:116775
X:-231, Y:6, Z:-119, T:116894
X:-231, Y:6, Z:-119, T:117023

2 个答案:

答案 0 :(得分:0)

我不确定,因为我本人仍在学习Python,但看来这可能是由于您最后的缩进所致。 它应该看起来像这样:

for i in range(len(zpeaks)-1):
        print(z[zpeaks[i]:zpeaks[i+1]])
        a = (x[zpeaks[i]:zpeaks[i+1]])
        b = (y[zpeaks[i]:zpeaks[i+1]])
        c = (z[zpeaks[i]:zpeaks[i+1]])
        pd.concat([pd.DataFrame(a),pd.DataFrame(b), pd.DataFrame(c)], axis=1).to_csv('Diff.csv', mode='w')

最后一行应位于for循环内,以便将每一行添加到csv中。

答案 1 :(得分:0)

问题在于,由于您的.to_csv调用在循环内,因此'Diff.csv'每次都会被覆盖。最终,只有最后一次写的内容。

有一些解决方案。

.to_csv(mode='a')

这使用附加模式,因此不会覆盖整个文件。您还需要指定header=None,以便它不会不断地在文件中间写入标题列。如果需要,可以在循环之前添加一次标题。

for i in range(len(zpeaks)-1):
    a = (x[zpeaks[i]:zpeaks[i+1]])
    b = (y[zpeaks[i]:zpeaks[i+1]])
    c = (z[zpeaks[i]:zpeaks[i+1]])
    pd.concat([pd.DataFrame(a), 
               pd.DataFrame(b), 
               pd.DataFrame(c)], axis=1).to_csv('Diff.csv', mode='a', header=None)

创建一个列表,在循环后进行连接

将您的DataFrames添加到循环中的列表中,然后在循环结束时进行连接,并将完整的DataFrame立即保存到文件中。

l = []
for i in range(len(zpeaks)-1):
    a = (x[zpeaks[i]:zpeaks[i+1]])
    b = (y[zpeaks[i]:zpeaks[i+1]])
    c = (z[zpeaks[i]:zpeaks[i+1]])
    l.append(pd.concat([pd.DataFrame(a),pd.DataFrame(b), pd.DataFrame(c)], axis=1))

#pd.concat(l).to_csv('Diff.csv')  # No column names
pd.concat(l).rename(columns=lambda x, y=iter(['x', 'y', 'z']): next(y)).to_csv('Diff.csv')