Merge branch 'master' of https://github.com/opensource9ja/danfojs

Author: risenW

.github/FUNDING.yml

@@ -0,0 +1,3 @@
+# These are supported funding model platforms
+
+patreon: danfojs

CODE_OF_CONDUCT.md

@@ -0,0 +1,76 @@
+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+In the interest of fostering an open and welcoming environment, we as
+contributors and maintainers pledge to making participation in our project and
+our community a harassment-free experience for everyone, regardless of age, body
+size, disability, ethnicity, sex characteristics, gender identity and expression,
+level of experience, education, socio-economic status, nationality, personal
+appearance, race, religion, or sexual identity and orientation.
+
+## Our Standards
+
+Examples of behavior that contributes to creating a positive environment
+include:
+
+* Using welcoming and inclusive language
+* Being respectful of differing viewpoints and experiences
+* Gracefully accepting constructive criticism
+* Focusing on what is best for the community
+* Showing empathy towards other community members
+
+Examples of unacceptable behavior by participants include:
+
+* The use of sexualized language or imagery and unwelcome sexual attention or
+ advances
+* Trolling, insulting/derogatory comments, and personal or political attacks
+* Public or private harassment
+* Publishing others' private information, such as a physical or electronic
+ address, without explicit permission
+* Other conduct which could reasonably be considered inappropriate in a
+ professional setting
+
+## Our Responsibilities
+
+Project maintainers are responsible for clarifying the standards of acceptable
+behavior and are expected to take appropriate and fair corrective action in
+response to any instances of unacceptable behavior.
+
+Project maintainers have the right and responsibility to remove, edit, or
+reject comments, commits, code, wiki edits, issues, and other contributions
+that are not aligned to this Code of Conduct, or to ban temporarily or
+permanently any contributor for other behaviors that they deem inappropriate,
+threatening, offensive, or harmful.
+
+## Scope
+
+This Code of Conduct applies both within project spaces and in public spaces
+when an individual is representing the project or its community. Examples of
+representing a project or community include using an official project e-mail
+address, posting via an official social media account, or acting as an appointed
+representative at an online or offline event. Representation of a project may be
+further defined and clarified by project maintainers.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported by contacting the project team at danfojs@gmail.com. All
+complaints will be reviewed and investigated and will result in a response that
+is deemed necessary and appropriate to the circumstances. The project team is
+obligated to maintain confidentiality with regard to the reporter of an incident.
+Further details of specific enforcement policies may be posted separately.
+
+Project maintainers who do not follow or enforce the Code of Conduct in good
+faith may face temporary or permanent repercussions as determined by other
+members of the project's leadership.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
+available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
+
+[homepage]: https://www.contributor-covenant.org
+
+For answers to common questions about this code of conduct, see
+https://www.contributor-covenant.org/faq

README.md

@@ -8,7 +8,8 @@
 ## danfojs: powerful javascript data analysis toolkit 
 ![Node.js CI](https://github.com/opensource9ja/danfojs/workflows/Node.js%20CI/badge.svg?branch=master)
 [![](https://data.jsdelivr.com/v1/package/npm/danfojs/badge?style=rounded)](https://www.jsdelivr.com/package/npm/danfojs)
-
+[![Build Status](https://travis-ci.org/opensource9ja/danfojs.svg?branch=master)](https://travis-ci.org/opensource9ja/danfojs)
+![Twitter](https://img.shields.io/twitter/url?style=social&url=https%3A%2F%2Ftwitter.com%2FDanfoJs) 
 
 
 ## What is it?

danfojs/src/core/frame.js

@@ -776,7 +776,7 @@ export class DataFrame extends Ndframe {
         let col_names = numeric_df.column_names
         let index = ['count', 'mean', 'std', 'min', 'median', 'max', 'variance']
 
-        let stats_arr = []
+        let stats_arr = {}
         col_names.forEach(name => {
             let col_series = numeric_df[name]
             let count = col_series.count()
@@ -788,9 +788,7 @@ export class DataFrame extends Ndframe {
             let variance = col_series.var()
 
             let _stats = [count, mean, std, min, median, max, variance]
-            let col_obj = {}
-            col_obj[name] = _stats
-            stats_arr.push(col_obj)
+            stats_arr[name] = _stats
 
         })
         let df = new DataFrame(stats_arr, { "index": index })
@@ -803,42 +801,36 @@ export class DataFrame extends Ndframe {
      * @param {include} scalar or array-like. A selection of dtypes or strings to be included. At least one of these parameters must be supplied.
      * @returns {DataFrame, Series} The subset of the frame including the dtypes.
      */
-    select_dtypes(include = [""]) {
+    select_dtypes(include) {
         let dtypes = this.dtypes
-        // let dtype_index = [...Array(this.dtypes.length - 1).keys()]
-        let col_vals = []
+        let col_names = this.column_names
+        let col_vals = {}
         let original_col_vals = this.col_data
-        const __supported_dtypes = ['float32', "int32", 'string', 'datetime']
+        const __supported_dtypes = ['float32', "int32", 'string', 'boolean']
 
-        if (include == [""] || include == []) {
+        if (include == undefined) {
             //return all
             let df = this.copy()
             return df
         } else {
             //check if the right types are included
             include.forEach(type => {
                 if (!__supported_dtypes.includes(type)) {
-                    throw Error(`Dtype Error: dtype ${type} not found in dtypes`)
+                    throw Error(`Dtype Error: dtype ${type} not supported.`)
                 }
-                dtypes.map((dtype, i) => {
-                    if (dtype == type) {
-                        let _obj = {}
-                        _obj[this.column_names[i]] = original_col_vals[i]
-                        col_vals.push(_obj)
-                    }
-                })
+            })
+
+
+            dtypes.forEach((dtype, i) => {
+                if (include.includes(dtype)) {
+                    console.log(dtype);
+                    col_vals[col_names[i]] = original_col_vals[i]
+                }
+            })
+            let df = new DataFrame(col_vals)
+            df.print()
+            return df
 
-            });
-            if (col_vals.length == 1) {
-                let _key = Object.keys(col_vals[0])[0]
-                let data = col_vals[0][_key]
-                let column_name = [_key]
-                let sf = new Series(data, { columns: column_name, index: this.index })
-                return sf
-            } else {
-                let df = new DataFrame(col_vals, { index: this.index })
-                return df
-            }
         }
 
     }
@@ -1209,6 +1201,7 @@ export class DataFrame extends Ndframe {
                 }
             })
 
+
             if (kwargs['columns'].length != kwargs['values'].length) {
                 throw Error(`Lenght Error: The lenght of the columns names must be equal to the lenght of the values,
                  got column of length ${kwargs['columns'].length} but values of length ${kwargs['values'].length}`)
@@ -1231,38 +1224,11 @@ export class DataFrame extends Ndframe {
 
             })
 
-            let final_data = []
+            let final_data = {}
             new_col_data.map((col, i) => {
-                let col_obj = {}
-                col_obj[this.column_names[i]] = col
-                final_data.push(col_obj)
+                final_data[this.column_names[i]] = col
             })
-            // let fil_idx = 0
-            // this.column_names.map((col, idx) => {
-            //     let _obj = {}
-            //     if (kwargs['columns'].includes(col)) {
-            //         console.log(fil_idx);
-            //         console.log(col);
-            //         console.log(kwargs['values'][fil_idx]);
-            //         let temp_col_data = this.col_data[idx]  //retreive the column data
-            //         let __temp = []
-            //         temp_col_data.map(val => {     //fill the column
-            //             if (isNaN(val) && typeof val != "string") {
-            //                 __temp.push(kwargs['values'][fil_idx])
-
-            //             } else {
-            //                 __temp.push(val)
-            //             }
-            //         })
-            //         fil_idx += 1
-            //         _obj[col] = __temp
-            //         new_col_data_obj.push(_obj)
-            //     } else {
-            //         _obj[col] = this.col_data[idx]
-            //         new_col_data_obj.push(_obj)
-            //     }
-
-            // })
+
             return new DataFrame(final_data, { index: this.index })
 
         } else {
@@ -1663,9 +1629,8 @@ export class DataFrame extends Ndframe {
             })
 
             if (utils.__key_in_object(kwargs, "replace") && utils.__key_in_object(kwargs, "with")) {
-                let new_col_data_obj = []
+                let new_col_data_obj = {}
                 this.column_names.map((col, idx) => {
-                    let _obj = {}
                     if (kwargs['in'].includes(col)) {
                         let temp_col_data = this.col_data[idx]  //retreive the column data
                         let __temp = []
@@ -1676,11 +1641,9 @@ export class DataFrame extends Ndframe {
                                 __temp.push(val)
                             }
                         })
-                        _obj[col] = __temp
-                        new_col_data_obj.push(_obj)
+                        new_col_data_obj[col] = __temp
                     } else {
-                        _obj[col] = this.col_data[idx]
-                        new_col_data_obj.push(_obj)
+                        new_col_data_obj[col] = this.col_data[idx]
                     }
                 })
                 return new DataFrame(new_col_data_obj, { columns: this.column_names, index: this.index })
@@ -1900,7 +1863,7 @@ export class DataFrame extends Ndframe {
         return plt
     }
 
-    
+
 
     /**
      * Returns the Tensorflow tensor backing the DataFrame Object
@@ -1963,11 +1926,9 @@ export class DataFrame extends Ndframe {
                 break;
         }
 
-        let new_col_obj = []
+        let new_col_obj = {}
         this.column_names.forEach((cname, i) => {
-            let _obj = {}
-            _obj[cname] = col_values[i]
-            new_col_obj.push(_obj)
+            new_col_obj[cname] = col_values[i]
         })
 
         let df = new DataFrame(new_col_obj, { dtypes: new_types, index: this.index })

danfojs/src/core/generic.js

@@ -33,10 +33,10 @@ export default class NDframe {
             this.series = false
             if (utils.__is_object(data[0])) { //check the type of the first object in the data
                 this.__read_object(data, 1) //type 1 object are of JSON form [{a: 1, b: 2}, {a: 30, b: 20}]
-            } else if (Array.isArray(data[0]) || utils.__is_number(data[0]) || utils.__is_string(data[0])) {
-                this.__read_array(data)
             } else if (utils.__is_object(data)) {
                 this.__read_object(data, 2)  //type 2 object are of the form {a: [1,2,3,4], b: [30,20, 30, 20}]
+            } else if (Array.isArray(data[0]) || utils.__is_number(data[0]) || utils.__is_string(data[0])) {
+                this.__read_array(data)
             } else {
                 throw "File format not supported for now"
             }
@@ -165,7 +165,7 @@ export default class NDframe {
     __set_col_types(dtypes, infer) {
         //set data type for each column in an NDFrame
         const __supported_dtypes = ['float32', "int32", 'string', 'boolean']
-       
+
 
         if (infer) {
             if (this.series) {
@@ -178,7 +178,7 @@ export default class NDframe {
                 this.col_types = utils.__get_t(this.col_data)
             }
         } else {
-            
+
             if (this.series) {
                 this.col_types = dtypes
                 this.col_data = [this.values]