Python chart: Minimum value

[jamescooper]

Not sure why this doesn't work?

import pandas as pd
from datetime import datetime
import matplotlib.pyplot as plt

today_format = datetime.strptime(datetime.today().strftime('%d/%m/%Y'), "%d/%m/%Y")
filtered_df = values=df['Current price'], aggfunc='min') & (df['Date Captured'] == today_format)]
filtered_df.plot(x="Mon Year", y=["Current price"], kind="bar")
plt.title("Minimum Price")
plt.xlabel("Month Year")
plt.ylabel("Price (£)")
plt.locator_params(axis='x', nbins=12)
plt.show()

 

[jamescooper]

Thank you so much, works great.

 

[Cubist]

Thank you so much, works great.

Consider "Marking a solution" to let others know you've found a solution and help others who have the same questions as you find the answer quickly without digging through pages of posts.

 

[jamescooper]

One final question on this code.

So on testing this finds the minimum value of all dates in the dataset for the date rather than the minimum value on today's date for that "Check-In" date.

Which bit would I change to resolve; I have made a few modifications to it.

Many thanks.

import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime
import datetime
import matplotlib.dates as mdates
import numpy as np
import matplotlib.ticker as plticker

today = datetime.datetime.today().date()
string_date = today.strftime("%b %y")

df["Date Captured"] = pd.to_datetime(df["Date Captured"])
df["Check-In"] = pd.to_datetime(df["Check-In"])
df_filtered = df[df["Date Captured"].dt.date == today]
df_filtered = df[df["Mon Year"]== string_date]
grouped = df_filtered.groupby("Check-In")["Current price"].min().reset_index()

fig, ax = plt.subplots()
p1 = ax.bar(grouped["Check-In"], grouped["Current price"], color='g')
ax.bar_label(p1, label_type="edge")
ax.bar_label(p1)

# Formatting the x-axis
ax.xaxis.set_major_formatter(mdates.DateFormatter("%a %d")) # Format as "Jan 2025"
loc = plticker.MultipleLocator(base=1.0) # this locator puts ticks at regular intervals
ax.xaxis.set_major_locator(loc)
plt.xlabel("Check-In Date")
plt.ylabel("Price (£)")
plt.title("February 25 - Minimum Price")
plt.xticks(rotation=90) # Rotate labels
plt.ylim(50, 150)
plt.show()

 

[Cubist]

df_filtered = df[df["Mon Year"]== string_date]

Try remove this line. I don't see the use of your "Mon Year" column. It seems like an unnecessary calculation. You can always use the code to format the the date as M-Y without adding a whole new column to your data set.

Like what you're doing here.

ax.xaxis.set_major_formatter(mdates.DateFormatter("%a %d")) # Format as "Jan 2025"

 

[jamescooper]

Try remove this line. I don't see the use of your "Mon Year" column. It seems like an unnecessary calculation. You can always use the code to format the the date as M-Y without adding a whole new column to your data set.

Like what you're doing here.

This is with and without the line you said to remove. Essentially in the "with" graph, the values £95 for 1st February for example is the lowest captured across all "Dates Captured" for that date. I want the minimum value on today, i.e. 17th February for 1st February, 2nd February etc...

Hope that helps.

 

[jamescooper]

So I've tried a few options here but it is getting the Minimum value of ALL "Date Captured" for a "Check-in" date rather than the minimum value today. This is my code:

import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime
import datetime
import matplotlib.dates as mdates
import numpy as np
import matplotlib.ticker as plticker

today = datetime.datetime.today().date()
string_date = today.strftime("%b %y")

df["Date Captured"] = pd.to_datetime(df["Date Captured"])
df["Check-In"] = pd.to_datetime(df["Check-In"])
df_filtered = df[df["Date Captured"].dt.date == today]
df_filtered = df[df["Mon Year"]== string_date]
grouped = df_filtered.groupby("Check-In")["Current price"].min().reset_index()

fig, ax = plt.subplots()
p1 = ax.bar(grouped["Check-In"], grouped["Current price"], color='g')
ax.bar_label(p1, label_type="edge")
ax.bar_label(p1)

# Formatting the x-axis
ax.xaxis.set_major_formatter(mdates.DateFormatter("%a %d")) # Format as "Jan 2025"
loc = plticker.MultipleLocator(base=1.0) # this locator puts ticks at regular intervals
ax.xaxis.set_major_locator(loc)
plt.xlabel("Check-In Date")
plt.ylabel("Price (£)")
plt.title("February 25 - Minimum Price")
plt.xticks(rotation=90) # Rotate labels
plt.ylim(50, 150)
plt.show()


Any thoughts appreciated.

 

[jamescooper]

Any thoughts, sorry?

 

[Cubist]

What's the difference between check-in and captured date?

 

[jamescooper]

"Check-in" date is the date of check in.

Date captured is when the data is captured, so for today it would be 20/02/2025.

 

[Cubist]

df_filtered = df[df["Date Captured"].dt.date == today]
df_filtered = df[df["Mon Year"]== string_date]

This is not working as you intended, the df_filtered is only filtering for "Mon Year" = string_date. The first filter gets overridden.

You need both simultaneously like this

df_filtered = df[(df["Date Captured"].dt.date == today) & (df["Mon Year"] == string_date)]