Python load_csv_frame示例

示例#1

文件： multivariate.py 项目： jpfairbanks/asonam2013

def multivariate_load(data_dir, post_proc_dir, timeindex, timepoint):
    """
    Arguments:
    =========
    - `data_dir` : where the data lives
    - `post_proc_dir` : where to put my output/cache
    - `timeindex`: the indices to load
    - `timepoint`: the time stamp of interest
    """
    ccf = kio.load_csv_frame(
        DATA_DIR, "local_clustering_coefficients", POST_PROC_DIR + "localcc.1.100.10.csv", TIMEINDEX
    )
    trif = kio.load_csv_frame(DATA_DIR, "triangles", POST_PROC_DIR + "triangles.1.100.10.csv", TIMEINDEX)
    bcf = kio.load_csv_frame(DATA_DIR, "betweenness_centrality", POST_PROC_DIR + "bc.1.100.10.csv", TIMEINDEX)
    namesf = pd.read_csv(DATA_DIR + "triangles.100.csv", header=None)
    names = namesf[[0, 1]].set_index(0)
    names[1].name = "name"
    triseq = trif[t]
    ccseq = ccf[t]
    bcseq = bcf[t]
    triseq.name = "tri"
    ccseq.name = "cc"
    bcseq.name = "bc"
    bcseq.dtype = np.float
    tf = names.join(triseq)
    tf = tf.join(ccseq)
    tf = tf.join(bcseq)
    return trif, ccf, bcf, namesf, tf

示例#2

文件： multivariate.py 项目： PardeshiSourabh/graphanalysis

def multivariate_load(data_dir, post_proc_dir, timeindex, timepoint):
    """
    Arguments:
    =========
    - `data_dir` : where the data lives
    - `post_proc_dir` : where to put my output/cache
    - `timeindex`: the indices to load
    - `timepoint`: the time stamp of interest
    """
    ccf = kio.load_csv_frame(DATA_DIR, 'local_clustering_coefficients',
                             POST_PROC_DIR + 'localcc.1.100.10.csv', TIMEINDEX)
    trif = kio.load_csv_frame(DATA_DIR, 'triangles',
                              POST_PROC_DIR + 'triangles.1.100.10.csv',
                              TIMEINDEX)
    bcf = kio.load_csv_frame(DATA_DIR, 'betweenness_centrality',
                             POST_PROC_DIR + 'bc.1.100.10.csv', TIMEINDEX)
    namesf = pd.read_csv(DATA_DIR + 'triangles.100.csv', header=None)
    names = namesf[[0, 1]].set_index(0)
    names[1].name = 'name'
    triseq = trif[t]
    ccseq = ccf[t]
    bcseq = bcf[t]
    triseq.name = 'tri'
    ccseq.name = 'cc'
    bcseq.name = 'bc'
    bcseq.dtype = np.float
    tf = names.join(triseq)
    tf = tf.join(ccseq)
    tf = tf.join(bcseq)
    return trif, ccf, bcf, namesf, tf

示例#3

文件： clustering_coefficients.py 项目： jpfairbanks/asonam2013

def load_data(data_dir, post_proc_dir, timeindex, timepoint):
    """
    Arguments:
    =========
    - `data_dir` : where the data lives
    - `post_proc_dir` : where to put my output/cache
    - `timeindex`: the indices to load
    - `timepoint`: the time stamp of interest
    """
    ccf    = kio.load_csv_frame(DATA_DIR, 'local_clustering_coefficients',
                             POST_PROC_DIR+'localcc.1.100.10.csv', TIMEINDEX)
    trif   = kio.load_csv_frame(DATA_DIR, 'triangles',
                             POST_PROC_DIR+'triangles.1.100.10.csv', TIMEINDEX)
    namesf = pd.read_csv(DATA_DIR+'triangles.100.csv', header=None)
    names = namesf[[0,1]].set_index(0)
    return trif, ccf, namesf

示例#4

def load_data(data_dir, post_proc_dir, timeindex, timepoint):
    """
    Arguments:
    =========
    - `data_dir` : where the data lives
    - `post_proc_dir` : where to put my output/cache
    - `timeindex`: the indices to load
    - `timepoint`: the time stamp of interest
    """
    ccf = kio.load_csv_frame(DATA_DIR, 'local_clustering_coefficients',
                             POST_PROC_DIR + 'localcc.1.100.10.csv', TIMEINDEX)
    trif = kio.load_csv_frame(DATA_DIR, 'triangles',
                              POST_PROC_DIR + 'triangles.1.100.10.csv',
                              TIMEINDEX)
    namesf = pd.read_csv(DATA_DIR + 'triangles.100.csv', header=None)
    names = namesf[[0, 1]].set_index(0)
    return trif, ccf, namesf