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python - Python Pandas 绘图警告

问题描述

当我在 spyder 中使用 pandas 绘图数据时。它总是会显示一条警告消息：

C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\indexing.py:494：SettingWithCopyWarning：试图在数据帧的切片副本上设置值。尝试使用 .loc[row_indexer,col_indexer] = value 代替。请参阅文档中的警告：http: //pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy self.obj[item] = s

我的脚本如下：

import pandas as pd

loc0 = r'D:\DC_BP00010.T0058_20190804_082758_15_14_PM2_1031.txt'
loc1 = r'D:\DC_BP00010.T0058_20190804_082758_17_16_PM1_1193.txt'

locs = [loc0,loc1]  # Update files in the list

parameters_must_be = ['Time', 'StepNo (Int)'] # Do not change this one
parameters = ["HeadBEPTrend1 (Float)"] # Key in parameters needed
parameters_all = parameters_must_be.append(parameters) 

endpoint_steps = [3] # Update endpoint steps in the list

Titles = 'BP00010' # Titles for plot

Colors = ['black','red','brown','crimson','olive','blue','yellow','darkorange','lime','purple','deeppink','dodgerblue','orange','indigo','darkslateblue','lawngreen','darkslategray','darkgreen','midnightblue','lightseagreen','gold','maroon','navy','teal']

dfs = []
sa = []
ss = []
axs = []
n = len(locs) # Number of datalog files

for i in range(0,n):
    dfs.append(pd.read_csv(locs[i], sep=('\t'), skiprows=6, usecols=parameters_all))
    ss.append(dfs[i][dfs[i]['StepNo (Int)'].isin(endpoint_steps)])
    sa.append(ss[i].loc[:,'Time']-ss[i].loc[:,'Time'].iloc[0])
    ss[i].loc[:,'Time'] = sa[i].loc[:]

ax=ss[0].plot(x='Time', y=parameters, title=Titles, color=Colors[0:len(parameters)], linewidth=1)

if n>1:
    for i in range(1,n):
        axs.append(ss[i].plot(x='Time', y=parameters, color=Colors[len(parameters)*i:len(parameters)*i+len(parameters)], linewidth=1, ax=ax))

ax.set_xlim(0,80)
ax.set_ylim(0,60)
ax.set_ylabel('Endpoint Intensity')
ax.legend(['BP00010#14','BP00010#15','BP00010#16','BP00010#17'], bbox_to_anchor=(1.31, .5), loc=5, borderaxespad=0.)

标签： pythonpandasplot

解决方案

ss[i].loc[:,'Time'] = sa[i].loc[:]导致错误：

  • 您正在尝试更改另一个数据框中的值。
  • ss是数据框列表
  • ss[i]是来自的特定数据框dfs

ss并且sa是从以下创建的部分数据框的列表：

  • ss.append(dfs[i][dfs[i]['StepNo (Int)'].isin(endpoint_steps)])
    • ss来自dfs
  • sa.append(ss[i].loc[:,'Time']-ss[i].loc[:,'Time'].iloc[0])
    • sa来自ss
  • 从其他数据框创建数据框很好，但这样做会引用原始数据，而不是副本。

.copy()创建时添加ss和sa：

  • ss.append(dfs[i][dfs[i]['StepNo (Int)'].isin(endpoint_steps)].copy())
  • sa.append(ss[i].loc[:,'Time']-ss[i].loc[:,'Time'].iloc[0].copy())

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