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How to conditionally sort X-axis values in Matplotlib plot?

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1

I have the following DataFrame:

file size
abc1.txt 2.1 MB
abc2.txt 1.0 MB
abc3.txt 1.5 MB
abc4.txt 767.9 KB

When I plot these data (plt.plot(df['file'],df['size'])), the values of KB and MB are obviously incorrectly ordered and are messed. How can I sort them so that the sorting would start from KB and would continue with MB?

767.9 KB 1.0 MB 1.5 MB 2.1 MB

python pandas matplotlib

share|improve this question

asked Mar 25 at 20:17

ScalaBoyScalaBoy

94555 silver badges2222 bronze badges

add a comment | 

0

1

I have the following DataFrame:

file size
abc1.txt 2.1 MB
abc2.txt 1.0 MB
abc3.txt 1.5 MB
abc4.txt 767.9 KB

When I plot these data (plt.plot(df['file'],df['size'])), the values of KB and MB are obviously incorrectly ordered and are messed. How can I sort them so that the sorting would start from KB and would continue with MB?

767.9 KB 1.0 MB 1.5 MB 2.1 MB

python pandas matplotlib

share|improve this question

asked Mar 25 at 20:17

ScalaBoyScalaBoy

94555 silver badges2222 bronze badges

add a comment | 

I have the following DataFrame:

file size
abc1.txt 2.1 MB
abc2.txt 1.0 MB
abc3.txt 1.5 MB
abc4.txt 767.9 KB

When I plot these data (plt.plot(df['file'],df['size'])), the values of KB and MB are obviously incorrectly ordered and are messed. How can I sort them so that the sorting would start from KB and would continue with MB?

767.9 KB 1.0 MB 1.5 MB 2.1 MB

python pandas matplotlib

share|improve this question

asked Mar 25 at 20:17

ScalaBoyScalaBoy

94555 silver badges2222 bronze badges

file size
abc1.txt 2.1 MB
abc2.txt 1.0 MB
abc3.txt 1.5 MB
abc4.txt 767.9 KB

767.9 KB 1.0 MB 1.5 MB 2.1 MB

share|improve this question

asked Mar 25 at 20:17

ScalaBoyScalaBoy

94555 silver badges2222 bronze badges

share|improve this question

asked Mar 25 at 20:17

ScalaBoyScalaBoy

94555 silver badges2222 bronze badges

asked Mar 25 at 20:17

ScalaBoyScalaBoy

94555 silver badges2222 bronze badges

asked Mar 25 at 20:17

ScalaBoyScalaBoy

94555 silver badges2222 bronze badges

2 Answers
2

active

oldest

votes

1

First it's reading your numbers as a string, so any order wouldn't really make much sense and further the the space between the points is not representative.

Also in general I'd say it's poor practice to have different units on the same axis. Better to convert to the same unit:

import matplotlib.pyplot as plt
import pandas as pd

df = pd.DataFrame([['abc1.txt', '2.1 MB'],
 ['abc2.txt', '1.0 MB'],
 ['abc3.txt', '1.5 MB'],
 ['abc4.txt', '767.9 KB']], columns=["file", 'size'])

# This is a list comprehension that splits the number out of the string, converts it to a float, 
# and divides it by 1000 if the other part of the string is 'KB'.
df['size_float'] = [float(x[0])/1000 if x[1]=='KB' else float(x[0]) for x in df['size'].str.split()]
plt.plot(df['file'],df['size_float'])

share|improve this answer

answered Mar 25 at 21:11

DeclanDeclan

9588 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Shouldn't I divide by 1024?
  
  – ScalaBoy
  Mar 25 at 21:16
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Lol, sure, if you want. :) It looks like your MB numbers are only accurate to one significant figure so it won't make much difference at the end of the day.
  
  – Declan
  Mar 25 at 21:20
  

  
  
  
  

add a comment | 

2

df = pd.DataFrame('file': [1,2,3,4], 'size': ['2.1 MB', '1.0 MB', '1.5 MB', '767.9 KB'])
cv= '': 1, 'KB': 1e1, 'MB': 1e6, 'GB': 1e9, 'TB': 1e12
df['size_bytes'] = df['size'].apply(lambda x: float(x.split()[0])*cv[x.split()[1]] 
 if len(x.split())==2 else float(x))
fig, ax = plt.subplots()
plt.plot(df['file'],df['size_bytes'])

And if you want the y axis in human readable form

def to_human_readable(size):
 power = 1000
 n = 0
 mem = 0 : '', 1: 'KB', 2: 'MB', 3: 'GB', 4: 'TB'
 while size > power:
 size /= power
 n += 1
 return "0 1".format(size, mem[n])

ax.set_yticklabels([to_human_readable(v) if v >= 0 else ' ' for v in 
 ax.get_yticks(minor=False)])

(In digital storage 1kb = 1000)

share|improve this answer

answered Mar 25 at 21:39

mujjigamujjiga

4,35522 gold badges1414 silver badges2222 bronze badges

add a comment | 

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1

First it's reading your numbers as a string, so any order wouldn't really make much sense and further the the space between the points is not representative.

Also in general I'd say it's poor practice to have different units on the same axis. Better to convert to the same unit:

import matplotlib.pyplot as plt
import pandas as pd

df = pd.DataFrame([['abc1.txt', '2.1 MB'],
 ['abc2.txt', '1.0 MB'],
 ['abc3.txt', '1.5 MB'],
 ['abc4.txt', '767.9 KB']], columns=["file", 'size'])

# This is a list comprehension that splits the number out of the string, converts it to a float, 
# and divides it by 1000 if the other part of the string is 'KB'.
df['size_float'] = [float(x[0])/1000 if x[1]=='KB' else float(x[0]) for x in df['size'].str.split()]
plt.plot(df['file'],df['size_float'])

share|improve this answer

answered Mar 25 at 21:11

DeclanDeclan

9588 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Shouldn't I divide by 1024?
  
  – ScalaBoy
  Mar 25 at 21:16
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Lol, sure, if you want. :) It looks like your MB numbers are only accurate to one significant figure so it won't make much difference at the end of the day.
  
  – Declan
  Mar 25 at 21:20
  

  
  
  
  

add a comment | 

1

First it's reading your numbers as a string, so any order wouldn't really make much sense and further the the space between the points is not representative.

Also in general I'd say it's poor practice to have different units on the same axis. Better to convert to the same unit:

import matplotlib.pyplot as plt
import pandas as pd

df = pd.DataFrame([['abc1.txt', '2.1 MB'],
 ['abc2.txt', '1.0 MB'],
 ['abc3.txt', '1.5 MB'],
 ['abc4.txt', '767.9 KB']], columns=["file", 'size'])

# This is a list comprehension that splits the number out of the string, converts it to a float, 
# and divides it by 1000 if the other part of the string is 'KB'.
df['size_float'] = [float(x[0])/1000 if x[1]=='KB' else float(x[0]) for x in df['size'].str.split()]
plt.plot(df['file'],df['size_float'])

share|improve this answer

answered Mar 25 at 21:11

DeclanDeclan

9588 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Shouldn't I divide by 1024?
  
  – ScalaBoy
  Mar 25 at 21:16
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Lol, sure, if you want. :) It looks like your MB numbers are only accurate to one significant figure so it won't make much difference at the end of the day.
  
  – Declan
  Mar 25 at 21:20
  

  
  
  
  

add a comment | 

First it's reading your numbers as a string, so any order wouldn't really make much sense and further the the space between the points is not representative.

Also in general I'd say it's poor practice to have different units on the same axis. Better to convert to the same unit:

import matplotlib.pyplot as plt
import pandas as pd

df = pd.DataFrame([['abc1.txt', '2.1 MB'],
 ['abc2.txt', '1.0 MB'],
 ['abc3.txt', '1.5 MB'],
 ['abc4.txt', '767.9 KB']], columns=["file", 'size'])

# This is a list comprehension that splits the number out of the string, converts it to a float, 
# and divides it by 1000 if the other part of the string is 'KB'.
df['size_float'] = [float(x[0])/1000 if x[1]=='KB' else float(x[0]) for x in df['size'].str.split()]
plt.plot(df['file'],df['size_float'])

share|improve this answer

answered Mar 25 at 21:11

DeclanDeclan

9588 bronze badges

import matplotlib.pyplot as plt
import pandas as pd

df = pd.DataFrame([['abc1.txt', '2.1 MB'],
 ['abc2.txt', '1.0 MB'],
 ['abc3.txt', '1.5 MB'],
 ['abc4.txt', '767.9 KB']], columns=["file", 'size'])

# This is a list comprehension that splits the number out of the string, converts it to a float, 
# and divides it by 1000 if the other part of the string is 'KB'.
df['size_float'] = [float(x[0])/1000 if x[1]=='KB' else float(x[0]) for x in df['size'].str.split()]
plt.plot(df['file'],df['size_float'])

share|improve this answer

answered Mar 25 at 21:11

DeclanDeclan

9588 bronze badges

answered Mar 25 at 21:11

DeclanDeclan

9588 bronze badges

answered Mar 25 at 21:11

DeclanDeclan

9588 bronze badges

2

df = pd.DataFrame('file': [1,2,3,4], 'size': ['2.1 MB', '1.0 MB', '1.5 MB', '767.9 KB'])
cv= '': 1, 'KB': 1e1, 'MB': 1e6, 'GB': 1e9, 'TB': 1e12
df['size_bytes'] = df['size'].apply(lambda x: float(x.split()[0])*cv[x.split()[1]] 
 if len(x.split())==2 else float(x))
fig, ax = plt.subplots()
plt.plot(df['file'],df['size_bytes'])

And if you want the y axis in human readable form

def to_human_readable(size):
 power = 1000
 n = 0
 mem = 0 : '', 1: 'KB', 2: 'MB', 3: 'GB', 4: 'TB'
 while size > power:
 size /= power
 n += 1
 return "0 1".format(size, mem[n])

ax.set_yticklabels([to_human_readable(v) if v >= 0 else ' ' for v in 
 ax.get_yticks(minor=False)])

(In digital storage 1kb = 1000)

share|improve this answer

answered Mar 25 at 21:39

mujjigamujjiga

4,35522 gold badges1414 silver badges2222 bronze badges

add a comment | 

2

df = pd.DataFrame('file': [1,2,3,4], 'size': ['2.1 MB', '1.0 MB', '1.5 MB', '767.9 KB'])
cv= '': 1, 'KB': 1e1, 'MB': 1e6, 'GB': 1e9, 'TB': 1e12
df['size_bytes'] = df['size'].apply(lambda x: float(x.split()[0])*cv[x.split()[1]] 
 if len(x.split())==2 else float(x))
fig, ax = plt.subplots()
plt.plot(df['file'],df['size_bytes'])

And if you want the y axis in human readable form

def to_human_readable(size):
 power = 1000
 n = 0
 mem = 0 : '', 1: 'KB', 2: 'MB', 3: 'GB', 4: 'TB'
 while size > power:
 size /= power
 n += 1
 return "0 1".format(size, mem[n])

ax.set_yticklabels([to_human_readable(v) if v >= 0 else ' ' for v in 
 ax.get_yticks(minor=False)])

(In digital storage 1kb = 1000)

share|improve this answer

answered Mar 25 at 21:39

mujjigamujjiga

4,35522 gold badges1414 silver badges2222 bronze badges

add a comment | 

df = pd.DataFrame('file': [1,2,3,4], 'size': ['2.1 MB', '1.0 MB', '1.5 MB', '767.9 KB'])
cv= '': 1, 'KB': 1e1, 'MB': 1e6, 'GB': 1e9, 'TB': 1e12
df['size_bytes'] = df['size'].apply(lambda x: float(x.split()[0])*cv[x.split()[1]] 
 if len(x.split())==2 else float(x))
fig, ax = plt.subplots()
plt.plot(df['file'],df['size_bytes'])

And if you want the y axis in human readable form

def to_human_readable(size):
 power = 1000
 n = 0
 mem = 0 : '', 1: 'KB', 2: 'MB', 3: 'GB', 4: 'TB'
 while size > power:
 size /= power
 n += 1
 return "0 1".format(size, mem[n])

ax.set_yticklabels([to_human_readable(v) if v >= 0 else ' ' for v in 
 ax.get_yticks(minor=False)])

(In digital storage 1kb = 1000)

share|improve this answer

answered Mar 25 at 21:39

mujjigamujjiga

4,35522 gold badges1414 silver badges2222 bronze badges

df = pd.DataFrame('file': [1,2,3,4], 'size': ['2.1 MB', '1.0 MB', '1.5 MB', '767.9 KB'])
cv= '': 1, 'KB': 1e1, 'MB': 1e6, 'GB': 1e9, 'TB': 1e12
df['size_bytes'] = df['size'].apply(lambda x: float(x.split()[0])*cv[x.split()[1]] 
 if len(x.split())==2 else float(x))
fig, ax = plt.subplots()
plt.plot(df['file'],df['size_bytes'])

def to_human_readable(size):
 power = 1000
 n = 0
 mem = 0 : '', 1: 'KB', 2: 'MB', 3: 'GB', 4: 'TB'
 while size > power:
 size /= power
 n += 1
 return "0 1".format(size, mem[n])

ax.set_yticklabels([to_human_readable(v) if v >= 0 else ' ' for v in 
 ax.get_yticks(minor=False)])

share|improve this answer

answered Mar 25 at 21:39

mujjigamujjiga

4,35522 gold badges1414 silver badges2222 bronze badges

answered Mar 25 at 21:39

mujjigamujjiga

4,35522 gold badges1414 silver badges2222 bronze badges

answered Mar 25 at 21:39

mujjigamujjiga

4,35522 gold badges1414 silver badges2222 bronze badges