This page shows how to use Python to read and parse text and CSV data with names and counts and make a simple bar chart.

Here are links to the topic series of representing and processing data.

• Summarizing book names and word count data
• Ways to represent table data

R examples:

• R: Bar chart from hard-coded data
• R: Bar chart from CSV
• R: Bar chart from JSON
• R: Bar chart from XML

Python examples:

•  Python: Bar chart from text and CSV (this page)
• Python: Bar chart from JSON
• Python: Bar chart from XML
• Python: Bar chart from CSV using Pandas
• Python: Bar chart from JSON using Pandas

JavaScript and D3 examples:

• JavaScript: SVG bar chart using D3

Julia examples:

• Julia: Bar chart from JSON data using StatsPlots

... more to be added ...

Here is the text data to be read.

The delimiter is the colon character ":".

Some required parameters can be assigned as variables.
txtFs1 = "./letters1.txt"
Some others are omitted. Defaults used.

To text is read from a file as text.
print("Read \"{0:s}\" as text:".format(txtFs1)) textF1 = open(txtFs1,"r") textText1 = textF1.read() textF1.close()

The text is processed to split and output.
# echo and transform data into needed form print("") print("\tLetter : Count") print("") dataList1 = [] textList1 = textText1.split("\n") for text2 in textList1: list2 = text2.split(":") name1 = list2[0] count1 = int(list2[1]) print("\t{0:s} : {1:,}".format(name1,count1)) dataList1.append([name1,count1])
Note the conversion of count1 from string to integer.

Here is the Python code [#4]
import matplotlib.pyplot as plt import numpy as np np.random.seed(0) # parameters txtFs1 = "./letters1.txt" # read text print("Read \"{0:s}\" as text:".format(txtFs1)) textF1 = open(txtFs1,"r") textText1 = textF1.read() textF1.close() # process text # echo and transform data into needed form print("") print("\tLetter : Count") print("") dataList1 = [] textList1 = textText1.split("\n") for text2 in textList1: list2 = text2.split(":") name1 = list2[0] count1 = int(list2[1]) print("\t{0:s} : {1:,}".format(name1,count1)) dataList1.append([name1,count1]) # transform data into needed form xData1 = [] yData1 = [] for name1,count1 in dataList1: xData1.append(name1) yData1.append(count1) # set plot parameters fontDict1 = { "family" : "Verdana", "weight" : "bold", "size" : 16 } plt.rc("font", **fontDict1) # make the bar chart rlen1 = 1 clen1 = 1 width1 = 1024 height1 = 360 dpi1 = 72 figsize1 = (width1/dpi1,height1/dpi1) fig1,ax1 = plt.subplots(rlen1,clen1,figsize=figsize1,dpi=dpi1) y_pos1 = np.arange(len(xData1)) plt.bar(y_pos1, yData1) plt.xticks(y_pos1, xData1) plt.ylabel("Count") plt.xlabel("Letter") plt.title("Count by Letter") # save the bar chart print("") pngFs1 = "./count13-4-01.png" print("{0:s} (chart as image)".format(pngFs1)) fig1.savefig(pngFs1,bbox_inches="tight")

Here is the output of the Python code.
Read "./letters1.txt" as text: Letter : Count a : 59,900 b : 11,302 c : 14,311 d : 34,483 e : 95,247 f : 17,852 g : 13,528 h : 62,509 i : 46,347 j : 2,321 k : 4,449 l : 25,939 m : 19,154 n : 51,311 o : 54,741 p : 9,918 q : 183 r : 37,468 s : 44,630 t : 72,396 u : 20,651 v : 7,458 w : 18,376 x : 376 y : 14,814 z : 234 ./count13-4-01.png (chart as image)

Here is the CSV data to be read.

Whenever custom handling of CSV files is required, a language such as Python can be used.

The csv module is required.
import csv

Some required parameters can be assigned as variables.
csvFs1 = "./letters1.csv" delimiter1 = "," quote1 = "\""
Some others are omitted. Defaults used.

The csv file is read and processing using the csv module. This is preferred as the delimiters, quotes, etc., are handled automatically.
print("Read \"{0:s}\" as csv.".format(csvFs1)) csvF1 = open(csvFs1,"r") reader1 = csv.reader(csvF1,delimiter=delimiter1,quotechar=quote1) csvList1 = list(reader1) csvF1.close()
In this case, the complete table is forced (eager evaluation) so that the file can be closed and processing done elsewhere.

The CSV file that has been read can now be read as a 2D table - a list of lists of values.
print("") print("\tLetter : Count") print("") for rpos1,rowList1 in enumerate(csvList1): name1 = rowList1[0] count1 = int(rowList1[1]) print("\t{0:s} : {1:,}".format(name1,count1))
Note the conversion of count1 from string to integer.

Here is the Python code [#9]
import matplotlib.pyplot as plt import numpy as np np.random.seed(0) import csv # parameters csvFs1 = "./letters1.csv" delimiter1 = "," quote1 = "\"" # read CSV print("Read \"{0:s}\" as csv.".format(csvFs1)) csvF1 = open(csvFs1,"r") reader1 = csv.reader(csvF1,delimiter=delimiter1,quotechar=quote1) csvList1 = list(reader1) csvF1.close() # process CSV print("") print("\tLetter : Count") print("") for rpos1,rowList1 in enumerate(csvList1): name1 = rowList1[0] count1 = int(rowList1[1]) print("\t{0:s} : {1:,}".format(name1,count1)) # transform data into intermediate form dataList1 = [] for rpos1,rowList1 in enumerate(csvList1): name1 = rowList1[0] count1 = int(rowList1[1]) dataList1.append([name1,count1]) # transform data into needed form xData1 = [] yData1 = [] for name1,count1 in dataList1: xData1.append(name1) yData1.append(count1) # set plot parameters fontDict1 = { "family" : "Verdana", "weight" : "bold", "size" : 16 } plt.rc("font", **fontDict1) # make the bar chart rlen1 = 1 clen1 = 1 width1 = 1024 height1 = 360 dpi1 = 72 figsize1 = (width1/dpi1,height1/dpi1) fig1,ax1 = plt.subplots(rlen1,clen1,figsize=figsize1,dpi=dpi1) y_pos1 = np.arange(len(xData1)) plt.bar(y_pos1, yData1) plt.xticks(y_pos1, xData1) plt.ylabel("Count") plt.xlabel("Letter") plt.title("Count by Letter") # save the bar chart print("") pngFs1 = "./count13-9-01.png" print("{0:s} (chart as image)".format(pngFs1)) fig1.savefig(pngFs1,bbox_inches="tight")

Here is the output of the Python code.
Read "./letters1.csv" as csv. Letter : Count a : 59,900 b : 11,302 c : 14,311 d : 34,483 e : 95,247 f : 17,852 g : 13,528 h : 62,509 i : 46,347 j : 2,321 k : 4,449 l : 25,939 m : 19,154 n : 51,311 o : 54,741 p : 9,918 q : 183 r : 37,468 s : 44,630 t : 72,396 u : 20,651 v : 7,458 w : 18,376 x : 376 y : 14,814 z : 234 ./count13-9-01.png (chart as image)

Note that csv files are stored and read as text. When it is important that certain data be numeric fields, explicit conversion is necessary.