Looping columns of data frame and plotting separately in Python

Question

Below is my code Snippet. I would like to plot each column at a time against time in a line plot. Each column in different plots But the plot seems to keep accumulating the older values in the bottom.

import os
import pandas as pd
import numpy as np
from matplotlib import pyplot
import matplotlib.pyplot as plt
import seaborn as sns; sns.set()


import re
def makeLinePlot(df):
    file_name="File Name not passed to this method"
    print("Ploting")
    df2=df
    fig,ax=plt.subplots(figsize=(30,8))
    i=0
    numRos = df.columns.size
    for colName in df.columns:
        i=i+1
        print(file_name,colName)
        df2[colName]=df2[colName].astype(float)
        print(colName,df2[colName].shape)
        g=sns.lineplot(x=df2.index, y=df2[colName], ax=ax)
        colNameR = re.sub('\W+','', colName )
        g.get_figure().savefig(colNameR+".png")


range = pd.date_range('2015-01-01', '2015-01-02', freq='1min')
df = pd.DataFrame(index = range)

# Average speed in miles per hour
df['speed'] = np.random.randint(low=0, high=60, size=len(df.index))
# Distance in miles (speed * 0.5 hours)
df['distance'] = df['speed'] * 0.25 
# Cumulative distance travelled
df['cumulative_distance'] = df.distance.cumsum()
makeLinePlot(df)

Answer 1

I have made some changes in your code and now it seems I have got what you want. Use the following code.

import os
import pandas as pd
import numpy as np
from matplotlib import pyplot
import matplotlib.pyplot as plt
import seaborn as sns; sns.set()


import re
def makeLinePlot(df):
    df2=df
    i=0

    numRos = df.columns.size

    fig,ax =plt.subplots( nrows=1, ncols=numRos,figsize=(30,8))

    for index, colName in enumerate(df.columns):
        i=i+1
        df2[colName]=df2[colName].astype(float)
        print(colName,df2[colName].shape)
        g=sns.lineplot(x=df2.index, y=df2[colName], ax=ax[index])
        colNameR = re.sub('\W+','', colName )
        g.get_figure().savefig(colNameR+".png")


range = pd.date_range('2015-01-01', '2015-01-02', freq='1min')
df = pd.DataFrame(index = range)

# Average speed in miles per hour
df['speed'] = np.random.randint(low=0, high=60, size=len(df.index))
# Distance in miles (speed * 0.5 hours)
df['distance'] = df['speed'] * 0.25 
# Cumulative distance travelled
df['cumulative_distance'] = df.distance.cumsum()
makeLinePlot(df)

I have got this.