小编Xav*_*zet的帖子

下面的代码与我以前使用的 csv 一起使用，两个 csv 的列数相同，并且列的名称相同。

在这里工作的 csv 的数据

此处没有的 csv 数据

这个错误是什么意思？为什么我收到这个错误？

from pandas import read_csv
from pandas import DataFrame
from pandas import Grouper
from matplotlib import pyplot

series = read_csv('carringtonairtemp.csv', header=0, index_col=0, parse_dates=True, squeeze=True)

groups = series.groupby(Grouper(freq='A'))
years = DataFrame()

for name, group in groups:
    years[name.year] = group.values

years = years.T

pyplot.matshow(years, interpolation=None, aspect='auto')
pyplot.show()

错误

from pandas import read_csv
from pandas import DataFrame
from pandas import Grouper
from matplotlib import pyplot

series = read_csv('carringtonairtemp.csv', header=0, …

您好，感谢您的帮助！（下面提供的代码和数据）（下图的图像）

我正在尝试向此热图添加一个图例，以解释地图上颜色的差异（较暖的颜色意味着较高的温度）。我添加：

ax1.legend([ax1], ['Temp'])

问题是这行代码不会导致我的绘图包含图例。我需要做什么才能添加解释温度和颜色之间关系的图例？

raw_data = pd.read_csv('https://raw.githubusercontent.com/the- 
datadudes/deepSoilTemperature/master/allStationsDailyAirTemp1.csv', index_col=1, parse_dates=True)
df_all_stations = raw_data.copy()

# load the data into a DataFrame, not a Series
# parse the dates, and set them as the index

df1 = df_all_stations[df_all_stations['Station'] == 'Williston']



# groupby year and aggregate Temp into a list
dfg1 = df1.groupby(df1.index.year).agg({'Temp': list})

# create a wide format dataframe with all the temp data expanded
df1_wide = pd.DataFrame(dfg1.Temp.tolist(), index=dfg1.index)


# adding the data between 1990/01/01 -/04/23 and delete the 29th of …

预先感谢您的帮助！

我正在尝试在 matplotlib 中创建箱线图，但在尝试添加标签时出现错误。这是引发错误的代码：

df_selected_station_D.boxplot(column='20 cm', by='Month',figsize=(15,5),grid=True, xlabel = 'x data');

这是它导致的错误：

TypeError: boxplot() got an unexpected keyword argument 'xlabel'

这个错误是什么意思以及为什么我会收到它？（完整代码和图片如下）

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import warnings
warnings.filterwarnings('ignore')


raw_data = pd.read_csv('all-deep-soil-temperatures.csv', index_col=1, parse_dates=True)
df_all_stations = raw_data.copy()

df_selected_station = df_all_stations[df_all_stations['Station'] == 'Minot']
df_selected_station.fillna(method = 'ffill', inplace=True);
df_selected_station_D=df_selected_station.resample(rule='D').mean()
df_selected_station_D['Day'] = df_selected_station_D.index.dayofyear

mean=df_selected_station_D.groupby(by='Day').mean()
mean['Day']=mean.index


df_selected_station_D['Month'] = df_selected_station_D.index.month
df_selected_station_D.head()

df_selected_station_D.boxplot(column='20 cm', by='Month',figsize=(15,5),grid=True);

您好，提前感谢您的帮助！

当我尝试执行从 GitHub 提取的时间序列分解时，出现ValueError: You Mustspecify a period or x must be a pandas object with a DatetimeIndex with a freq not set to None 。我想我对该错误有了基本的了解，但是当我直接从我的计算机上的文件中提取数据而不是从 GitHub 中提取数据时，我没有收到此错误。为什么只有当我从 GitHub 提取数据时才会出现此错误？我应该如何更改我的代码才能不再出现此错误？

import pandas as pd
import numpy as np 
%matplotlib inline
from statsmodels.tsa.seasonal import seasonal_decompose

topsoil = pd.read_csv('https://raw.githubusercontent.com/the- 
datadudes/deepSoilTemperature/master/meanDickinson.csv',parse_dates=True)

topsoil = topsoil.dropna()
topsoil.head()

topsoil.plot();

result = seasonal_decompose(topsoil['Topsoil'],model='ad')


from pylab import rcParams
rcParams['figure.figsize'] = 12,5
result.plot();