How to plot a line graph with many lines from excel-CodePudding

I want to plot the line graph with so many lines. I found the below basic commend to plot 1 line.

import matplotlib.pyplot as plt
location_3='C:\\Users\\Poon\\Downloads\\20211014_SBS_BEMS\\1043 final.csv'
csvfiles_3=glob.glob(location_3)
df7=pd.DataFrame()
for file_new_3 in csvfiles_3: 
    df7=pd.read_csv(file_new_3,skiprows=[0])
    print(df7)
    ax=plt.plot(df7.iloc[:, 1],df7.iloc[:, 2],'g')

But I need to plot more than 100 lines. Is there a faster way? Here are some of my data set in excel. There is more column than I show.

19/5/2019 0:00  237 64.93   82.35   16.15   46.88   18.11   148.3115
19/5/2019 1:00  237.2667    64.93   82.35   16.15   46.88   18.11   148.3295
19/5/2019 2:00  238 64.93   82.35   16.15   46.88   18.11   148.348
19/5/2019 3:00  238 64.93   82.35   16.15   46.88   18.11   148.3672
19/5/2019 4:00  238 64.93   82.35   16.15   46.88   18.11   148.4432
19/5/2019 5:00  238 64.93   82.35   16.15   46.88   18.11   148.7437
19/5/2019 6:00  238 64.93   82.35   16.15   46.88   18.11   149.064
19/5/2019 7:00  238 64.93   82.35   16.15   46.88   18.11   149.3825
19/5/2019 8:00  238 64.93   82.35   16.15   46.88   18.11   149.7037
19/5/2019 9:00  238.7833    64.93   82.35   16.15   46.88   18.11   150.0222
19/5/2019 10:00 239 64.93   82.35   16.15   46.88   18.11   150.3422
19/5/2019 11:00 239 64.93   82.35   16.15   46.88   18.11   150.6617
19/5/2019 12:00 239 64.93   82.35   16.15   46.88   18.11   150.9813
19/5/2019 13:00 239 64.93   82.35   16.15   46.88   18.11   151.3018
19/5/2019 14:00 239 64.93   82.35   16.15   46.88   18.11   151.6213
19/5/2019 15:00 239 64.93   82.35   16.15   46.88   18.11   151.94
19/5/2019 16:00 239.4167    64.93   82.35   16.15   46.88   18.11   152.2615
19/5/2019 17:00 240 64.93   82.35   16.15   46.88   18.11   152.5812
19/5/2019 18:00 240 64.93   82.35   16.15   46.88   18.11   152.8295
19/5/2019 19:00 240 64.93   82.35   16.15   46.88   18.11   152.8608
19/5/2019 20:00 240 64.93   82.35   16.15   46.88   18.11   152.8797
19/5/2019 21:00 240 64.93   82.35   16.15   46.88   18.11   152.8962
19/5/2019 22:00 240 64.93   82.35   16.15   46.88   18.11   152.9148
19/5/2019 23:00 240.05  64.93   82.35   16.15   46.88   18.11   152.9337
20/5/2019 0:00  241 64.93   82.35   16.15   46.88   18.11   152.9508

So What I want is the x-axis to be the date, and Y-axis is column 2, then 3,4....until the end.

Moreover, the x-axis needs to reduce the number of plot ticks. Now there are too many plot ticks. How can I reduce them to "only year"? For example, there should be only 2019,2020,2021,2022.

Thanks a lots guys for your help.

CodePudding user response：

Hi and welcome to Stackoverflow. You can use the below code to read the data (I just copied the data you provided and edited it for a couple of years and the data points to increase over time), then create the plots and finally add the timeline in years in the X-axis. The dataframe has Date as header for first date column and the other data columns are named A through G. The legend has some text, but you can edit it as you need.

import pandas as pd
import matplotlib.pyplot as plt
import datetime
import matplotlib.dates as mdates

df=pd.read_excel("inputfile.xlsx")
df['Date'] = pd.to_datetime(df['Date'])

plt.plot(df.Date, df.A, label = "line 1")
plt.plot(df.Date, df.B, label = "line 2")
plt.plot(df.Date, df.C, label = "line 3")
plt.plot(df.Date, df.D, label = "line 4")
plt.plot(df.Date, df.E, label = "line 5")
plt.plot(df.Date, df.F, label = "line 6")
plt.plot(df.Date, df.G, label = "line 7")

plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y'))
plt.gca().xaxis.set_major_locator(mdates.YearLocator())
plt.legend()
plt.show()

Output pic

CodePudding user response：

If you want to generate lines automatically, you can use a for cycle leaving out xaxis column like this (added example data for clearance, you can still read from your file):

import matplotlib.pyplot as plt
import matplotlib.dates as mdates

data = {
  "date": ['19/5/2019 0:00', '19/5/2019 1:00', '19/5/2020 2:00', '20/5/2021 3:00', '21/5/2022 1:00'],
  "colA": [237, 237, 238, 237, 240],
  "colB": [64.93, 64.94, 64.95, 65.52, 65.32],
  "colC": [644.93, 644.94, 644.95, 654.52, 654.32]
}

df = pd.DataFrame(data)

df.date=pd.to_datetime(df.date)

plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y'))
plt.gca().xaxis.set_major_locator(mdates.YearLocator())

for col in df.columns:
    if not col == 'date':
        plt.plot(df.date, df[col], label=col) 
        
plt.legend()
plt.show()

Result:

Extra note: you can add base to YearLocator to change the frequency of years, for example, every 5 years would be:

plt.gca().xaxis.set_major_locator(mdates.YearLocator(base=5))