Understanding Creating Histograms in Python

I would like to histogram multiple csv data in python.
The script below is for histograming data from one csv file.

import pandas as pd
import matplotlib.pyplot asplt

df = pd.read_csv("default_list_1.csv")

df = df ['detime' ]
df.hist()

# Add Title
plt.title('detime_count')

# Score on the x-axis and freq on the y-axis
plt.xlabel ('detime')
plt.ylabel('count')
plt.show()

How do I change the script to stack data from multiple csv files in this histogram?
The default_list_0.csv ranges from default_list_1.csv to default_list_1000.csv.
I would like to use a single histogram to represent all of this data.

I apologize for the rudimentary content, but I appreciate your cooperation.

python

2022-09-30 19:56

2 Answers

This is an example of code when you want to build columns for each data file.
1000 If I arrange 1000 pieces, I won't know what's going on.

[Example code]

import pandas as pd
import matplotlib.pyplot asplt

df1 = pd.read_csv("S:\\work\\w041_python\\default_list_1.csv")
df2 = pd.read_csv("S:\\work\\w041_python\\default_list_2.csv")

df1 = df1 ['detime']
df2 = df2 ['detime']
# df.hist()

labels = ['list_1', 'list_2' ]
plt.hist([df1,df2], label=labels)
plt.legend()
# Add Title
plt.title('detime_count')

# Score on the x-axis and freq on the y-axis
plt.xlabel ('detime')
plt.ylabel('count')
plt.show()

Examples of code are default_list_1.csv and default_list_2.csv.
Read the pathname of the file passed to read_csv appropriately.

[default_list_1.csv]

detime
1
2
3
3

[default_list_2.csv]

detime
1
2
2
1
2

[Output results]

2022-09-30 19:56

import pandas as pd
import matplotlib.pyplot asplt

df = pd.concat(
    [pd.read_csv("default_list_{}.csv".format(i+1))) for i in range(1000)])
df = df ['detime' ]
df.hist()
plt.title('detime_count')
plt.xlabel ('detime')
plt.ylabel('count')
plt.show()

2022-09-30 19:56

If you have any answers or tips

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