How do I add index rows in Python beginner Pandas?

Asked 2 weeks ago, Updated 2 weeks ago, 8 views

Not applicable to iloc, etc.

There's only pure data, and when it's called in, The top index is 0,1,2,3,4 and not a data value.I want to put the same basic index as .

I can use the header command, is that right?

pandas

2022-09-19 23:22

1 Answers

>>> import pandas as pd
>>> import numpy as np
>>> df = pd.util.testing.makeDataFrame()
>>> df
                   A         B         C         D
SIGmzXtCmx  0.470768 -0.807193  0.468051  0.488866
E3IKjzhosa -0.236880 -0.888015 -1.600056 -0.199805
lD7Ht3xkVP -0.193062  0.322076 -1.094081  0.582686
7q5Brj9AeQ -1.361694 -1.420203 -1.140609 -1.733826
Ojwcgiv4n0 -0.727904 -0.149616  0.971487 -0.534119
liAo28WDHV -1.884758  1.971477 -0.435113 -0.373316
ynChzER1cX  1.933783  0.460862  1.399503  0.850038
tkk5R6susD  1.072193 -0.883758  1.023936 -0.336794
DjOYPTEpsQ  0.621182  0.536783  0.800621  0.698601
PwZWRLp0nx -0.773563 -0.621115 -0.731001 -0.550074
aCXd4qbqIE -0.217936  0.402844 -0.182283  0.975230
PwL0VM1tA5  0.658788  1.239632  1.545079  0.493019
4JaTLCc42P  0.816992  0.603847 -0.453202 -1.096263
wYYuleUYGh  0.986658  1.271412 -0.427188 -0.084533
D2Ip7GZsUM  1.206546 -0.844979 -0.486307 -0.245169
CqQuk6SnnD -0.004026  0.224801  0.345854  1.917603
AxdW5Lr344  0.667752 -0.241325  0.831370 -0.746942
BYCczu7eNB -1.308622 -0.761518 -0.618947  0.495343
Red66rCMCD -1.186703  0.771694 -0.973173 -0.295230
W2JwIPenhL  1.140977 -1.138799 -0.900574  2.199128
Rgt6LLWqMJ  1.236587  0.546710 -0.172605 -0.553494
zpoOSKvHL9 -0.124489  0.707197 -0.997226 -1.298666
SHEhdSCuS3  0.287685 -1.249335 -0.415259 -0.156002
xkvdqJFapJ  1.392805 -0.291524  0.464281  0.003749
lnXyD12sVF -1.280195 -2.139832  0.017224 -0.502024
2CTYCniPfH -0.387830  0.960747 -2.074247  0.252334
DWm73dPY4y  0.083914 -0.523869 -0.961064  1.735112
5I3apS1Y3T -0.115769  1.869465 -1.615079  1.480948
i8HWgP7qCy  1.184549  0.086129 -1.461264  1.682370
lHX2TkmWtq  0.792383  1.170700 -0.969357 -0.392937
>>> df = df.set_index(np.array(range(len(df)))+1)
>>> df
           A         B         C         D
1   0.470768 -0.807193  0.468051  0.488866
2  -0.236880 -0.888015 -1.600056 -0.199805
3  -0.193062  0.322076 -1.094081  0.582686
4  -1.361694 -1.420203 -1.140609 -1.733826
5  -0.727904 -0.149616  0.971487 -0.534119
6  -1.884758  1.971477 -0.435113 -0.373316
7   1.933783  0.460862  1.399503  0.850038
8   1.072193 -0.883758  1.023936 -0.336794
9   0.621182  0.536783  0.800621  0.698601
10 -0.773563 -0.621115 -0.731001 -0.550074
11 -0.217936  0.402844 -0.182283  0.975230
12  0.658788  1.239632  1.545079  0.493019
13  0.816992  0.603847 -0.453202 -1.096263
14  0.986658  1.271412 -0.427188 -0.084533
15  1.206546 -0.844979 -0.486307 -0.245169
16 -0.004026  0.224801  0.345854  1.917603
17  0.667752 -0.241325  0.831370 -0.746942
18 -1.308622 -0.761518 -0.618947  0.495343
19 -1.186703  0.771694 -0.973173 -0.295230
20  1.140977 -1.138799 -0.900574  2.199128
21  1.236587  0.546710 -0.172605 -0.553494
22 -0.124489  0.707197 -0.997226 -1.298666
23  0.287685 -1.249335 -0.415259 -0.156002
24  1.392805 -0.291524  0.464281  0.003749
25 -1.280195 -2.139832  0.017224 -0.502024
26 -0.387830  0.960747 -2.074247  0.252334
27  0.083914 -0.523869 -0.961064  1.735112
28 -0.115769  1.869465 -1.615079  1.480948
29  1.184549  0.086129 -1.461264  1.682370
30  0.792383  1.170700 -0.969357 -0.392937


2022-09-19 23:22

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