預先感謝您的幫助?。ㄏ旅娴拇a）（鏈接到第一個數據）（鏈接到我要添加的數據）我正在嘗試從第二個 CSV（上圖）導入數據，并根據該 CSV 數據向該圖添加第二行。執行此操作的最佳方法是什么？（下圖）圖上的波浪線代表數據的范圍。import pandas as pdimport numpy as npimport matplotlib.pyplot as pltimport warningswarnings.filterwarnings('ignore')raw_data = pd.read_csv('all-deep-soil-temperatures.csv', index_col=1, parse_dates=True)df_all_stations = raw_data.copy()selected_soil_station = 'Minot'df_selected_station = df_all_stations[df_all_stations['Station'] == selected_soil_station]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.dayofyearmean=df_selected_station_D.groupby(by='Day').mean()mean['Day']=mean.indexmaxx=df_selected_station_D.groupby(by='Day').max()minn=df_selected_station_D.groupby(by='Day').min()mean['maxx20']=maxx['20 cm']mean['minn20']=minn['20 cm']plt.style.use('ggplot')bx = mean.plot(x='Day', y='20 cm',color='black')plt.fill_between(mean['Day'],mean['minn20'],mean['maxx20'],color='blue',alpha = 0.2);bx.set_xlabel("Day of the year")bx.set_ylabel("Temperature in Celsius")bx.set_title("Soil Temp, Air Temp, and Snow Depth for " + str(selected_soil_station))我擁有的：我想要擁有什么：
1 回答
料青山看我應如是
TA貢獻1772條經驗 獲得超8個贊
查看新代碼的內聯符號
刪除是
plt.style.use('ggplot')因為很難看到fill_between顏色不要
;在 python 中使用將其他文件中的數據加載到單獨的數據框中
根據需要清理并聚合新數據
將日期列設置為日期時間格式
提取一年中的某一天
groupby一年中的某一天和總計mean,?min, 和max溫度
將新數據繪制為
axes與原始圖相同的圖，bx。
df_all_stations = pd.read_csv('data/so_data/2020-09-29 64128817/all-deep-soil-temperatures.csv', index_col=1, parse_dates=True)
# load air temp data
at = pd.read_csv('data/so_data/2020-09-29 64128817/allStationsDailyAirTemp1.csv')
# set Date to a datetime format
at.Date = pd.to_datetime(at.Date)
# extract day of year
at['doy'] = at.Date.dt.dayofyear
# selet data from Minot
at = at[at.Station == 'Minot']
# groupby the day of year (doy) and aggregate min max and mean
atg = at.groupby('doy')['Temp'].agg([min, max, 'mean'])
selected_soil_station = 'Minot'
df_selected_station = df_all_stations[df_all_stations['Station'] == selected_soil_station].copy()? # make a copy here, otherwise there will be warning
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
maxx=df_selected_station_D.groupby(by='Day').max()
minn=df_selected_station_D.groupby(by='Day').min()
mean['maxx20']=maxx['20 cm']
mean['minn20']=minn['20 cm']
bx = mean.plot(x='Day', y='20 cm', color='black', figsize=(9, 6), label='20 cm Soil Temp')
plt.fill_between(mean['Day'], mean['minn20'], mean['maxx20'], color='blue', alpha = 0.2, label='20 cm Soil Temp Range')
# add air temp plot to the bx plot with ax=bx
atg['mean'].plot(ax=bx, label='Mean Air Temp')
# add air temp fill between plot to the bx plot
bx.fill_between(atg.index, atg['min'], atg['max'], color='cyan', alpha = 0.2, label='Air Temp Range')
bx.set_xlabel("Day of the year")
bx.set_ylabel("Temperature in Celsius")
bx.set_title("Soil Temp, Air Temp, and Snow Depth for " + str(selected_soil_station))
# grid
bx.grid()
# set legend location
bx.legend(bbox_to_anchor=(1.05, 1), loc='upper left')
# remove margin spaces
plt.margins(0, 0)
plt.show()
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