Python reads csv, Excel files to generate charts

import pandas
import  as plt
# Set the csv file path
file = r'E:\'
# Prevent garbled Chinese characters
['-serif'] = ['Microsoft YaHei']
# Read the contents of a file via pandas
df = pandas.read_csv(file)
# Set the first line of the file to the sequence name
series_names = df .columns
# Plotting document data as line graphs
(df)
(series_names)  # Set the sequence name
('Horizontal axis title')     #Set the name of the horizontal coordinate
('Vertical axis title')     # Set the name of the vertical coordinate
('Chart Title')      # Setting the chart title
# Display the plotted charts on the screen
()
# Save the chart as a png file
# ('')

import pandas
import  as plt
# Set the csv file path
file = r'E:\'
# Prevent garbled Chinese characters
['-serif'] = ['Microsoft YaHei']
# Read the contents of a file via pandas
df = pandas.read_csv(file)
# Set the first line of the file to the sequence name
series_names = df .columns
# Define the size of the chart (length 15, height 8), must be placed in the front
(figsize=(15,8))
# Plotting document data as line graphs
(df, marker='o', markersize=3)  #marker sets marker style and size
('Horizontal axis title')   #Set the name of the horizontal coordinate
('Vertical axis title')   # Set the name of the vertical coordinate
('Chart Title')    # Setting the chart title
()              # Show gridlines
(series_names)  # Set the sequence name
(y=2, color='r', linestyle='--')   # Add a horizontal reference line on the y-axis.
(x=1, color='r', linestyle='--')   # Add a vertical reference line on the x-axis.
# Display the plotted charts on the screen
()
# Save the chart as a png file
# ('')

import pandas as pd
import  as plt
# Read data from CSV file and specify first row as column name
data = pd.read_csv(r'E:\', header=0)
# Prevent garbled Chinese characters
['-serif'] = ['Microsoft YaHei']
# Get the column name and corresponding value
columns = 
values = [0].values
# Plotting bar charts
(columns, values)
('Horizontal axis title')
('Vertical axis title')
('Chart Title')
# Display the plotted charts on the screen
()
# Save the chart as a png file
# ('')

import pandas as pd
import  as plt
# Read data from CSV file and specify first row as column name
data = pd.read_csv(r'E:\', header=0)
# Prevent garbled Chinese characters
['-serif'] = ['Microsoft YaHei']
# Define the size of the chart (length 15, height 8), must be placed in the front
(figsize=(15,8))
# Get the column name and corresponding value
columns = 
values = [0].values
# Plotting bar charts
(columns, values,    # Horizontal axis coordinates
        color='y',          # Set the column color (yellow, see color code)
        width = 0.8,        # Setting the column width
        edgecolor='k',      # Set the column border color (black, see color code)
        linewidth=2         # Setting the column border width
)
('Horizontal axis title')
('Vertical axis title')
('Chart Title')
# Display the plotted charts on the screen
()
# Save the chart as a png file
# ('')

import pandas
import  as plt
# Prevent garbled codes
['-serif'] = ['Microsoft YaHei']
# Read the contents of an Excel file
df = pandas.read_excel(r'E:\', sheet_name='Sheet1')
column_names = ()  # Get the name of line 1
excel_rows = [0]            # Get the number of rows
# Set the horizontal axis data, you can get in Excel, here directly traverse the number of rows from the beginning of 1 to the end
x = [i for i in range(1, excel_rows+1)]
# Iterate over the first row of column names
for col_name in column_names:
    # Extract data for drawing by column name
    y = df[col_name].to_numpy()
    # Draw a diagram, execute the horizontal axis coordinates, set the line legend name to the column name of the first row
    (x, y, label=col_name)
# Setting Properties
()  # Show legend title
('Name of the horizontal coordinate')
('Name of vertical coordinate')
('Line Chart Title')
# ('. /') # Save the picture
()  # View Pictures

import pandas
import  as plt
# Prevent garbled codes
['-serif'] = ['Microsoft YaHei']
# Read the contents of the Excel file, if reading a csv file, use pandas.read_csv
df = pandas.read_excel(r'E:\', sheet_name='Sheet1')
column_names = ()  #Read the name of line 1
excel_rows = [0]             # of lines read
# Define the size of the chart (length 15, height 8), must be placed in the front
(figsize=(15,8))
# Set the horizontal axis data, you can get in Excel, here directly traverse the number of rows from the beginning of 1 to the end
x = [i for i in range(1, excel_rows+1)]
# Iterate over the first row of column names
for col_name in column_names:
    # Extract data for drawing by column name
    y = df[col_name].to_numpy()
    # Draw a diagram, execute the horizontal axis coordinates, set the line legend name to the column name of the first row
    (x, y, label=col_name, marker='o', markersize=3)    #marker sets marker style and size
# Setting Properties
()  # Show legend title
('Name of the horizontal coordinate')
('Name of vertical coordinate')
('Line Chart Title')
()              # Show gridlines
(y=2, color='r', linestyle='--')   # Add a horizontal reference line on the y-axis
(x=1, color='r', linestyle='--')   # Add a vertical reference line on the x-axis
# ('. /') # Save the picture
()  # View Pictures

import pandas
import  as plt
# Prevent garbled codes
['-serif'] = ['Microsoft YaHei']
# Read the contents of an Excel file
df = pandas.read_excel(r'E:\', sheet_name='Sheet1')
# Get the name of the first line
column_names = ()
# Remove the first line and transpose the data
data = 
# Create a bar chart, specifying the type of plotting as a bar chart (line: line chart (default), bar: bar chart, barh: horizontal bar chart, hist: histogram, box: box line chart, kde: kernel density estimation chart, density: density chart, area: area chart, scatter: scatter chart, hexbin: Hexbin chart (used to show the distribution of two-dimensional data)
(kind='bar')
# Set the name of the column (rotation rotates the column heading by degrees)
(range(len(column_names)), column_names, rotation=0)
# Add title and axis labels
('Chart Title')
('Horizontal axis title')
('Vertical axis title')
# Display bar graphs
()

import pandas
import  as plt
# Prevent garbled codes
['-serif'] = ['Microsoft YaHei']
# Read the contents of an Excel file
df = pandas.read_excel(r'E:\', sheet_name='Sheet2')
# Get the name of the first line
column_names = ()
# Remove the first line and transpose the data
data = 
# Create a bar chart, specifying the type of plotting as a bar chart (line: line chart (default), bar: bar chart, barh: horizontal bar chart, hist: histogram, box: box line chart, kde: kernel density estimation chart, density: density chart, area: area chart, scatter: scatter chart, hexbin: Hexbin chart (used to show the distribution of two-dimensional data)
(kind='bar')
# Set the name of the column (rotation rotates the column heading by degrees)
(range(len(column_names)), column_names, rotation=0)
# Add title and axis labels
('Chart Title')
('Horizontal axis title')
('Vertical axis title')
# Modify the legend name (start with 1, 1 means row 1 data...)
handles, labels = ().get_legend_handles_labels()
labels = [int(label)+1 for label in labels]
(handles, labels)
# Display bar graphs
()

import pandas
import  as plt
# Prevent garbled codes
['-serif'] = ['Microsoft YaHei']
# Read the contents of an Excel file
df = pandas.read_excel(r'E:\', sheet_name='Sheet1')
# Set the image size (length 15, width 8)
fig = (figsize=(15, 8))
ax = fig.add_subplot()
# Get the name of the first line
column_names = ()
# Remove the first line and transpose the data
data = 
# Create bar charts
(
    kind='bar', # Specify the type of plotting as a histogram (line: line plot (default), bar: bar chart, barh: horizontal bar chart, hist: histogram, box: box line plot, kde: kernel density estimation plot, density: density plot, area: area plot, scatter: scatter plot, hexbin: Hexbin plot (used to show the two-dimensional data distribution)
    color='y',  # Set the column color (yellow, see color code)
    width=0.8,  # Set the column width
    edgecolor='k',  # Set the column border color (black, see color code)
    linewidth=2,    # Setting the column border width
    ax=ax           #Set the image size
)
# Set the name of the column (rotation rotates the column heading by degrees)
(range(len(column_names)), column_names, rotation=0)
# Add title and axis labels
('Chart Title')
('Horizontal axis title')
('Vertical axis title')
# Display bar graphs
()

from MarkupPy import markup
# Add images, set length and width
page = ()
('<img src="./" alt="csv-generated line graphs" width="800" height="500">')
# Write the file
with open('./', 'w') as file:
    (str(page))

import pandas
import  as plt
from MarkupPy import markup
# Set the csv file path
file = r'E:\'
# Prevent garbled Chinese characters
['-serif'] = ['Microsoft YaHei']
# Read the contents of a file via pandas
df = pandas.read_csv(file)
# Set the first line of the file to the sequence name
series_names = df .columns
# Plotting document data as line graphs
(df)
(series_names)  # Set the sequence name
('Horizontal axis title')     #Set the name of the horizontal coordinate
('Vertical axis title')     # Set the name of the vertical coordinate
('Chart Title')      # Setting the chart title
# Save the chart as a png file
('./')
# Add a picture
page = ()
('<img src="./" alt="csv-generated line graphs" width="800" height="500">')
# Write the file
with open('./', 'w') as file:
    (str(page))