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--- round_vs._format [2023/02/13 23:07] – raju
+++ print_hundredths [2023/02/14 20:45] – removed - external edit (Unknown date) 127.0.0.1
@@ Line 1: / Line 1: @@
-===== round vs. format =====
-==== write simple data ====
-<code>
-$ ipython
-Python 3.10.9 | packaged by conda-forge | (main, Jan 11 2023, 15:15:40) [MSC v.1916 64 bit (AMD64)]
-IPython 8.8.0 -- An enhanced Interactive Python. Type '?' for help.
-In [1]:
-a = 10.30467
-In [2]:
-'{:.2f}'.format(a)
-Out[2]:
-'10.30'
-In [3]:
-type('{:.2f}'.format(a))
-Out[3]:
-str
-In [4]:
-round(a,2)
-Out[4]:
-.3
-In [5]:
-type(round(a,2))
-Out[5]:
-float
-</code>
-Conclusions:
-  * The output of round is a floating point number. The output of format is a string
-  * To output dollars and pennies, format expression is better than rounding as it always gives the same number of digits after the decimal point.
-==== Write data into csv files ====
-Create some sample data
-<code>
-$ ipython
-Python 3.10.9 | packaged by conda-forge | (main, Jan 11 2023, 15:15:40) [MSC v.1916 64 bit (AMD64)]
-IPython 8.8.0 -- An enhanced Interactive Python. Type '?' for help.
-In [1]:
-import pandas as pd
-df = pd.DataFrame({'symbol': ['A', 'B', 'C', 'D'], 'price': [8.222, 7.007, 3.971, 9.801], 'change': [6.601, 7.241, -9.341, 48.001]})
-df
-Out[1]:
-  symbol  price  change
-      A  8.222   6.601
-      B  7.007   7.241
-      C  3.971  -9.341
-      D  9.801  48.001
-</code>
-If you round and dump the data to a file, it does not align around the decimal point
-<code>
-In [2]:
-df.round({'price':2, 'change': 2}).to_csv('x/foo1.csv', index=False, lineterminator='\n')
-</code>
-<code>
-$ cat ~/x/foo1.csv
-symbol,price,change
-A,8.22,6.6
-B,7.01,7.24
-C,3.97,-9.34
-D,9.8,48.0
-$ cat ~/x/foo1.csv | column -t -s, -R 2,3
-symbol  price  change
-A        8.22     6.6
-B        7.01    7.24
-C        3.97   -9.34
-D         9.8    48.0
-</code>
-But if we format the data, it can be aligned easily
-<code>
-In [3]:
-formats = {'price': '{:.2f}', 'change': '{:.2f}'}
-df2 = df.copy()
-for col, f in formats.items():
-    df2[col] = df2[col].apply(lambda x: f.format(x))
-df2.to_csv('x/foo2.csv', index=False, lineterminator='\n')
-</code>
-<code>
-$ cat ~/x/foo2.csv
-symbol,price,change
-A,8.22,6.60
-B,7.01,7.24
-C,3.97,-9.34
-D,9.80,48.00
-$ cat ~/x/foo2.csv | column -t -s, -R 2,3
-symbol  price  change
-A        8.22    6.60
-B        7.01    7.24
-C        3.97   -9.34
-D        9.80   48.00
-</code>
-Ref:- https://stackoverflow.com/questions/20003290/output-different-precision-by-column-with-pandas-dataframe-to-csv - shows how to format different columns with different precision.
-tags | print two digits after decimal, float_format by column