CODEWITHSUNDEEP
pythonpandasdataframematplotlib
fjurt
fjurt

Reputation: 793

Plot many time-series columns in one graph

I have a big dataframe with roughly 100 columns and I'm trying to plot all the time-series in one graph. Is there an easy way to deal with it, without specifying every y-axis manually?

This would be a simple example with these time-series: 02K W, 03K W, and 04K W:

import pandas as pd
import matplotlib.pyplot as plt

df1 = pd.DataFrame({
    'Date':['2021-01-01', '2021-01-02', '2021-01-03', '2021-01-04', '2021-01-05'],
    'index':[0, 1, 2, 3, 4], 
    '02K W':[3.5, 0.1, 3, 'nan', 0.2], 
    '03K W':[4.2, 5.2, 2.5, 3.0, 0.6], 
    '04K W':[1.5, 2.6, 8.2, 4.2, 5.3]}) 

df1['Date'] = pd.to_datetime(df1['Date'])
df1 = df1.set_index('index')

So far, I manually specify all y-axis to plot the individual time-series.

plt.plot(df1['Date'], df1['02K W'])
plt.plot(df1['Date'], df1['03K W'])
plt.plot(df1['Date'], df1['04K W'])

Is there a more elegant way to specify the relevant columns for the plot?

Upvotes: 1

Views: 3675

Answers (3)

tdy
tdy

Reputation: 41487

Is there a more elegant way to specify the relevant columns for the plot? ... [I'm trying] to plot everything except the index & date column.

Set Date as the index, which will overwrite the current index index. That will leave all columns except index and Date, so you can just use DataFrame.plot:

df1.set_index('Date').plot()

Or as Quang commented, use x='Date':

df1.plot(x='Date')

Note that you have a 'nan' string in your sample data. If this is true in your real data, you should convert those to the real np.nan, e.g., with pd.to_numeric or DataFrame.replace.

Upvotes: 1

mozway
mozway

Reputation: 262634

You can melt your columns and use seaborn.lineplot:

import seaborn as sns

sns.lineplot(data=df1.replace('nan', float('nan')).melt(id_vars=['Date']),
             x='Date', y='value', hue='variable'
            )

output:

lineplot

Upvotes: 1

fgacon
fgacon

Reputation: 111

import pandas as pd
import matplotlib.pyplot as plt

df1 = pd.DataFrame({
    'Date':['2021-01-01', '2021-01-02', '2021-01-03', '2021-01-04', '2021-01-05'],
    'index':[0, 1, 2, 3, 4], 
    '02K W':[3.5, 0.1, 3, 'nan', 0.2], 
    '03K W':[4.2, 5.2, 2.5, 3.0, 0.6], 
    '04K W':[1.5, 2.6, 8.2, 4.2, 5.3]}) 

df1['Date'] = pd.to_datetime(df1['Date'])
df1 = df1.set_index('index')

for col in df1.colums[1:]:
    plt.plot(df1['Date'], df1[col])

Upvotes: 1

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