└── README.md


/README.md:
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  1 | SAS to Python guide
  2 | ===================
  3 | 
  4 | `proc freq`
  5 | -----------
  6 | 
  7 | ```SAS
  8 | proc freq data=mydata;
  9 |     tables myvar / nocol nopercent nocum;
 10 | run;
 11 | ```
 12 | 
 13 | ```python
 14 | mydata.myvar.value_counts().sort_index()
 15 | ```
 16 | 
 17 | 
 18 | #### sort by frequency ####
 19 | 
 20 | ```SAS
 21 | proc freq order=freq data=mydata;
 22 | 	tables myvar / nocol nopercent nocum;
 23 | run;
 24 | ```
 25 | 
 26 | ```python
 27 | mydata.myvar.value_counts()
 28 | ```
 29 | 
 30 | 
 31 | #### with missing ####
 32 | 
 33 | ```SAS
 34 | proc freq order=freq data=mydata;
 35 |     tables myvar / nocol nopercent nocum missing;
 36 | run;
 37 | ```
 38 | 
 39 | ```python
 40 | mydata.myvar.value_counts(dropna=False)
 41 | ```
 42 | 
 43 | 
 44 | `proc means`
 45 | ------------
 46 | 
 47 | ```SAS
 48 | proc means data=mydata n mean std min max p25 median p75;
 49 |     var myvar;
 50 | run;
 51 | ```
 52 | 
 53 | ```python
 54 | mydata.myvar.describe()
 55 | ```
 56 | 
 57 | 
 58 | #### more percentiles ####
 59 | 
 60 | ```SAS
 61 | proc means data=mydata n mean std min max p1 p5 p10 p25 median p75 p90 p95 p99;
 62 | 	var myvar;
 63 | run;
 64 | ```
 65 | 
 66 | ```python
 67 | mydata.myvar.describe(percentiles=[.01, .05, .1, .25, .5, .75, .9, .95, .99])
 68 | ```
 69 | 
 70 | 
 71 | `data` step
 72 | -----------
 73 | 
 74 | #### concatenate datasets ####
 75 | 
 76 | ```SAS
 77 | data concatenated;
 78 |     set mydata1 mydata2;
 79 | run;
 80 | ```
 81 | 
 82 | ```python
 83 | concatenated = pandas.concat([mydata1, mydata2])
 84 | ```
 85 | 
 86 | 
 87 | `proc contents`
 88 | ---------------
 89 | 
 90 | ```SAS
 91 | proc contents data=mydata;
 92 | run;
 93 | ```
 94 | 
 95 | ```python
 96 | mydata.info()
 97 | ```
 98 | 
 99 | #### save output ####
100 | 
101 | ```SAS
102 | proc contents noprint data=mydata out=contents;
103 | run;
104 | ```
105 | 
106 | ```python
107 | contents = mydata.info()  # check this is right
108 | ```
109 | 
110 | 
111 | Misc
112 | ----
113 | 
114 | #### number of rows in a datastep ####
115 | 
116 | ```SAS
117 | * haha nice try. Try this for size: http://www2.sas.com/proceedings/sugi26/p095-26.pdf;
118 | ```
119 | 
120 | ```python
121 | len(mydata)
122 | ```
123 | 


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